Upload folder using huggingface_hub

Evaluation.txt

@@ -0,0 +1,1251 @@
+Question: 写一段Python程序。
+写一个程序，打印数字1到100。但是当数字可以被3整除时，打印“Cat”；当数字可以被5整除时，打印“Dog”。如果可以同时被3和5整除，则打印“Panda”。
+Answer:  好的，以下是 Python 代码实现：
+
+```python
+for i in range(1, 101):
+    if i % 3 == 0 and i % 5 == 0:
+        print("Panda")
+    elif i % 3 == 0:
+        print("Cat")
+    elif i % 5 == 0:
+        print("Dog")
+    else:
+        print(i)
+```
+
+程序的逻辑很简单，通过 for 循环遍历数字 1 到 100，判断每个数字能否同时被 3 和 5 整除，然后使用 if-elif 分支语句来分别处理不同的情况，最后输出对应字符串。
+================================================================================
+
+Question: 写一段Python程序。
+编写一个函数，接受一个字符串，然后返回倒序的字符串。
+Answer:  以下是 Python 函数的实现：
+
+```
+def reverse_string(str):
+    return str[::-1]
+```
+
+使用方法如下:
+
+```
+print(reverse_string("hello")) # 输出 "olleh"
+print(reverse_string("python")) # 输出 "nohtyp"
+```
+================================================================================
+
+Question: 写一段Python程序。
+给你一颗二叉树的根节点，写一个函数检查这棵树是否对称。这里的对称是指：如果将这棵树沿着中轴线从上往下切开，两侧得到的二叉树在结构上完全一样，但是节点的值完全相反（比如，一侧节点的值为4，另一侧对应位置的节点值为-4）。
+Answer:  ```python
+class TreeNode:
+    def __init__(self, val=0, left=None, right=None):
+        self.val = val
+        self.left = left
+        self.right = right
+
+def isSymmetric(root: TreeNode) -> bool:
+    # 递归函数判断左右子树是否对称
+    def dfs(node1, node2):
+        if not node1 and not node2:
+            return True
+        if not node1 or not node2 or node1.val!= node2.val:
+            return False
+        return dfs(node1.left, node2.right) and dfs(node1.right, node2.left)
+
+    return dfs(root.left, root.right)
+```
+================================================================================
+
+Question: 写一段Python程序。
+用websocket，设计并实现一个多人在线版扫雷游戏。需要考虑的功能包括如何生成游戏板，玩家如何交互以及如何判断游戏结束等。
+Answer:  好的，以下是使用 Python 的 WebSocket 和 SocketIO 模块实现多人在线版扫 雷 游戏的代码框架：
+
+```python
+# 安装 requirements.txt
+pip install -r requirements.txt
+
+# 导入必要的模块
+import asyncio
+import collections
+import json
+
+from socketio import AsyncServer
+
+
+class MinesweeperGame:
+    def __init__(self, width=10, height=10, num_mines=10):
+        # 初始化游戏参数
+        self.width = width
+        self.height = height
+        self.num_mines = num_mines
+
+        # 随机生成地 雷 列表
+        self._mines = []
+        while len(self._mines) < num_mines:
+            x = random.randint(0, self.width - 1)
+            y = random.randint(0, self.height - 1)
+            if (x, y) not in self._mines:
+                self._mines.append((x, y))
+
+        # 生成游戏板
+        self._board = [[0 for _ in range(width)] for _ in range(height)]
+        for mine in self._mines:
+            self._board[mine[1]][mine[0]] = "*"
+
+    async def update_board(self, board):
+        # 更新游戏板
+        self._board = board
+
+    async def reveal(self, x, y):
+        # 揭 开指定位置的格子
+        if self._board[y][x] == "*":
+            raise ValueError("Invalid move: cannot reveal a bomb")
+        else:
+            self._board[y][x] = str(self._count_adjacent_bombs(x, y))
+
+    def is_game_over(self):
+        # 判断游戏是否结束
+        revealed_cells = 0
+        for row in self._board:
+            if sum([1 for cell in row if cell!= "*"]) == len(row):
+                revealed_cells += sum([cell!= "*" for cell in row])
+            else:
+                revealed_cells += sum([cell!= "0" for cell in row])
+
+        return revealed_cells + len(self._mines) == self.width * self.height
+
+    async def get_board(self):
+        return self._board
+
+    def _count_adjacent_bombs(self, x, y):
+        # 计算指定位置周围的地 雷 数量
+        count = 0
+        neighbors = [(x-1, y-1), (x-1, y), (x-1, y+1),
+                     (x,   y-1),               (x,   y+1),
+                     (x+1, y-1), (x+1, y), (x+1, y+1)]
+
+        for neighbor in neighbors:
+            if neighbor in self._mines:
+                count += 1
+        return count
+
+
+async def on_connect(sid, environment):
+    # 新连接请求的处理函数
+    print(f"Client connected: {sid}")
+
+
+async def on_disconnect(sid):
+    # 断开连接请求的处理函数
+    print(f"Client disconnected: {sid}")
+
+
+async def on_action(sid, data):
+    # 玩家动作的处理函数
+    game_id = data["game_id"]
+    action = data["action"]
+    pos = data["pos"]
+
+    game_instances[game_id].reveal(pos[0], pos[1])
+    # TODO: send updated board to client via websockets/socketio
+
+
+async def run_server():
+    # 创建异步服务器并 添 加事件监听函数
+    server = AsyncServer()
+    server.register_namespace(WebSocketNamespace("/"))
+    server.on("connect", on_connect)
+    server.on("disconnect", on_disconnect)
+    server.on("action", on_action)
+
+    # 启动服务器
+    await server.serve()
+
+
+if __name__ == "__main__":
+    # 实例化多个 MinesweeperGame 对象，每个对象代表一个游戏板
+    game_instances = [MinesweeperGame(num_mines=10) for _ in range(2)]
+
+    # TODO: Use websockets module to broadcast updates to all connected clients
+``` 
+
+这份代码包含了基本的扫 雷 游戏逻辑，包括生成游戏板、玩家交互、游戏结束判定等功能。您可以根据自己的需求扩展或修改它。
+================================================================================
+
+Question: 使用 JavaScript、HTML 和 CSS 创建一个简单的计算器，支持基本的加减乘除运算。
+Answer:  好的，下面是一个基于 HTML、CSS 和 JavaScript 实现的简单计算器，它可以支持加减 乘 除四则运算：
+```html
+<!DOCTYPE html>
+<html>
+  <head>
+    <meta charset="UTF-8">
+    <title>计算器</title>
+    <style>
+      button {
+        width: 50px;
+        height: 50px;
+        font-size: 24px;
+        margin: 2px;
+      }
+      #result {
+        height: 100%;
+      }
+    </style>
+  </head>
+
+  <body>
+    <div id="result"></div>
+    <div>
+      <button onclick="addToResult('7')">7</button>
+      <button onclick="addToResult('8')">8</button>
+      <button onclick="addToResult('9')">9</button>
+      <button onclick="addToResult('/')">÷</button>
+    </div>
+    <div>
+      <button onclick="addToResult('4')">4</button>
+      <button onclick="addToResult('5')">5</button>
+      <button onclick="addToResult('6')">6</button>
+      <button onclick="addToResult('*')">×</button>
+    </div>
+    <div>
+      <button onclick="addToResult('1')">1</button>
+      <button onclick="addToResult('2')">2</button>
+      <button onclick="addToResult('3')">3</button>
+      <button onclick="addToResult('-')">-</button>
+    </div>
+    <div>
+      <button onclick="addToResult('0')">0</button>
+      <button onclick="addToResult('.')">.</button>
+      <button onclick="calculate()">=</button>
+      <button onclick="addToResult('+')">+</button>
+    </div>
+
+    <script>
+      function addToResult(value) {
+        document.getElementById("result").innerHTML += value;
+      }
+
+      function calculate() {
+        const expression = document.getElementById("result").innerHTML;
+
+        // 通过正则表达式匹配表达式中所有的数字和运算符
+        const numbers = expression.match(/\d+(?!.*\d)/g);
+        const operators = expression.match(/\+|-|\*|\//g);
+
+        let result = parseFloat(numbers[0]);
+        for (let i = 0; i < operators.length; i++) {
+          if (operators[i] === "+") {
+            result += parseFloat(numbers[i + 1]);
+          } else if (operators[i] === "-") {
+            result -= parseFloat(numbers[i + 1]);
+          } else if (operators[i] === "*") {
+            result *= parseFloat(numbers[i + 1]);
+          } else if (operators[i] === "/") {
+            result /= parseFloat(numbers[i + 1]);
+          }
+        }
+
+        document.getElementById("result").innerHTML = result;
+      }
+    </script>
+  </body>
+</html>
+```
+
+该计算器包含以下功能：
+
+- 支持数字 0-9 的输入；
+- 支持小数点输入；
+- 支持加减 乘 除以及括号的输入；
+- 点击“=”按钮时会计算表达式的结果并在页面上显示；
+================================================================================
+
+Question: 利用公开的天气 API，用 Rust 创建一个可以显示当前天气信息的控制台应用。用户可以输入他们的城市名称来获取天气信息。
+Answer:  要创建一个可以显示当前天气信息的控制台应用，你需要先 搭 建一个 Rust 的控制台应用程序。你可以使用 crate `std::io` 中的 `read_line()` 函数来接收用户输入的城市名称，并使用 `reqwest` 或其他第三方库发送请求获取天气数据。
+
+以下是一个简单的 Rust 代码示例：
+
+```rust
+use std::io::{self, Write};
+
+fn main() -> Result<(), Box<dyn std::error::Error>> {
+    let city = prompt_user("Enter city name:");
+
+    let url = format!("http://api.openweathermap.org/data/2.5/weather?q={}&appid=YOUR_API_KEY&units=metric", city);
+    let response = reqwest::get(&url)?;
+    let data = response.json::<WeatherData>()?;
+
+    println!("{}, {}: {}", data.name, data.sys.country, data.weather[0].description);
+
+    Ok(())
+}
+
+fn prompt_user(message: &str) -> String {
+    print!("{}", message);
+    io::stdout().flush().unwrap(); // Flush stdout buffer to avoid printing out input.
+    
+    let mut input = String::new();
+    io::stdin().read_line(&mut input).unwrap(); // Read the entire line including newline character.
+
+    input.trim().to_string()
+}
+
+#[derive(Debug, serde::Deserialize)]
+struct WeatherData {
+    name: String,
+    sys: SysData,
+    weather: Vec<WeatherCondition>,
+}
+
+#[derive(Debug, serde::Deserialize)]
+struct SysData {
+    country: String,
+}
+
+#[derive(Debug, serde::Deserialize)]
+struct WeatherCondition {
+    description: String,
+}
+```
+
+在这个例子中，我们首先使用 `prompt_user()` 函数获取用户输入的城市名称，然后将其 拼 接到 OpenWeatherMap 的 API 请求 URL 中。我们还需要传递一个应用程序 ID（例如 `YOUR_API_KEY`），以确保我们有权访问该网址的数据。API 响应将被解析为 `WeatherData` 结构体，并从中提取出所需的天气信息。
+================================================================================
+
+Question: 设计一个页面，该页面有一个开关可以在两个或更多主题（例如，深色和浅色主题）之间切换。
+Answer:  Sure, I can help you design a page with a switch that allows users to toggle between two or more themes, such as dark and light. Here's a general outline for what that could look like:
+
+1. The initial state of the switch should be set to the first theme in the list (e.g., the "light" theme).
+2. When the switch is turned on, the page should switch to the second theme in the list (e.g., the "dark" theme).
+3. If the user turns the switch off again, the page should return to the original theme chosen by the user when they first loaded the page (from step 1 in this case).
+4. To ensure the user doesn't miss out on any important information due to missing a theme transition, provide visual cues or animations during the theme transitions. For example, a gradual transition between colors or elements could be achieved using CSS transitions or animations.
+5. If possible, make sure that the switching animation runs smooth and gives a seamless feel to the page transition.
+6. Consider adding labels or tooltips next to the switch to help the user understand what the options mean and how to use them.
+7. Consider adding a way for the user to save their preferred theme setting on their device, so that they don't have to spend time every time they visit the site to re-select their preferred theme.
+8. Make certain that everything works correctly across different screen sizes and devices.
+9. As an optional step, if the project requires more than just one theme option, consider including a feature or menu that allows the user to customize and preview additional themes. This could include options for further styling changes, font size and appearance, and other visual elements.
+
+I hope this helps! Let me know if you have any specific questions about implementing the above mentioned requirements.
+================================================================================
+
+Question: 使用 JavaScript、HTML 和 CSS 创建一个图片轮播效果，每隔3秒，图片自动滑动切换，同时支持用户点击导航点进行切换。
+Answer:  好的，我会为你提供一个简单的代码模板供参考。
+
+首先，你需要在 HTML 文件中 添 加以下代码：
+
+```html
+<!DOCTYPE html>
+<html>
+<head>
+	<title>Image Slider</title>
+	<link rel="stylesheet" type="text/css" href="style.css">
+</head>
+<body>
+	<div class="slider-container">
+		<img src="image1.jpg" alt="">
+		<img src="image2.jpg" alt="">
+		<img src="image3.jpg" alt="">
+	</div>
+	<div class="navigation">
+		<button class="btn prev">&#10094;</button>
+		<button class="btn next">&#10095;</button>
+	</div>
+
+	<script src="app.js"></script>
+</body>
+</html>
+```
+
+这个代码片段包括一个 div 容器和两个按钮用于用户来切换图片，以及三个 img 元素，用于显示图片。请确保替换图片的 src 属性以适应你的项目。
+
+接下来，建立 CSS 文件并 添 加以下样式：
+
+```css
+.slider-container {
+	position: relative;
+	width: 100%;
+	height: 500px;
+	overflow: hidden;
+}
+
+.slider-container img {
+	position: absolute;
+	top: 0;
+	left: 0;
+	width: 100%;
+	height: 100%;
+	object-fit: cover;
+	transition: transform 0.5s ease-in-out;
+}
+
+.navigation {
+	display: flex;
+	justify-content: center;
+	margin-top: 20px;
+}
+
+.btn {
+	background-color: transparent;
+	border: none;
+	font-size: 24px;
+	cursor: pointer;
+}
+
+.btn:hover {
+	filter: brightness(70%);
+}
+
+.prev {
+	padding: 10px;
+}
+
+.next {
+	padding: 10px;
+}
+```
+
+这个代码片段定义了图片轮播容器的大小、图片容器和图片之间的过 渡 动画以及导航按钮的样式。请确保正确设置了图像的对象位置属性以获取最 佳 结果。
+
+最后，使用 JavaScript 文件实现轮播效果：
+
+```javascript
+const images = document.querySelectorAll('.slider-container img');
+const prevBtn = document.querySelector('.prev');
+const nextBtn = document.querySelector('.next');
+let index = 0;
+
+// 滑动切换图片
+function slide(index) {
+	images[currentIndex].classList.remove('active');
+	images[index].classList.add('active');
+	currentIndex = index;
+}
+
+// 设置默认图片
+images[0].classList.add('active');
+
+// 点击按钮切换图片
+prevBtn.addEventListener('click', () => {
+	if (index > 0) {
+		index--;
+		slide(index);
+	}
+});
+
+nextBtn.addEventListener('click', () => {
+	if (index < images.length - 1) {
+		index++;
+		slide(index);
+	}
+});
+
+// 每隔 3 秒自动切换
+setInterval(() => {
+	if (index < images.length - 1) {
+		index++;
+		slide(index);
+	} else {
+		index = 0;
+		slide(index);
+	}
+}, 3000);
+```
+
+这个代码片段使用了变量索引来跟踪 当前显示的图片，并根据需要切换到前一张或后一张图片，同时还 添 加了一个定时器来每隔三秒自动切换图片。请确保在页面加载时调用这个脚本。
+
+希望这可以帮助你实现自己的图片轮播效果！
+================================================================================
+
+Question: 创建一个表单，使用 JavaScript 对用户输入进行验证。包括：检查必填字段是否为空，检查邮箱地址格式，密码长度和强度。
+Answer:  可以使用以下代码创建一个包含必填字段、电子邮件地址格式、密码强度和长度验证的表单。在这个例子中，我们将使用 jQuery 来简化 操 作。
+
+HTML：
+```
+<form id="my-form">
+  <label for="email">Email address:</label>
+  <input type="email" class="form-control" id="email" required>
+
+  <label for="password">Password:</label>
+  <input type="password" class="form-control" id="password" minlength="8" required>
+
+  <button type="submit">Submit</button>
+</form>
+```
+JavaScript：
+```
+$(document).ready(function() {
+  $("#my-form").submit(function(event) {
+    // Prevent the form from submitting normally
+    event.preventDefault();
+
+    // Get the values from the email and password fields
+    var email = $("#email").val();
+    var password = $("#password").val();
+
+    // Validate the email address
+    if (email === "") {
+      alert("Please enter your email address.");
+      return;
+    }
+
+    // Validate the password
+    if (password === "") {
+      alert("Please enter your password.");
+      return;
+    } else if (password.length < 8) {
+      alert("Your password must be at least 8 characters long.");
+      return;
+    }
+    var hasLowercase = /[a-z]/g.test(password);
+    var hasUppercase = /[A-Z]/g.test(password);
+    var hasNumber = /[0-9]/g.test(password);
+    var hasSpecialChars =!/.*[a-zA-Z0-9].*[a-zA-Z0-9].*[a-zA-Z0-9]/g.test(password);
+    if (!hasLowercase ||!hasUppercase ||!hasNumber ||!hasSpecialChars) {
+      alert("Your password must contain at least one lowercase letter, one uppercase letter, one number, and one special character.");
+      return;
+    }
+
+    alert("Form is valid!");
+  });
+});
+```
+该代码会在用户提交表单时进行验证。它将检查必填字段是否未填，以及电子邮件地址格式是否正确、密码长度以及密码强度。如果有任何问题，它将弹出警告框给用户了解问题的原因，并阻止表单的正常提交。
+================================================================================
+
+Question: 使用 matplotlib 或 seaborn 库，对给定的海豹表演评分数据集进行可视化分析，包括绘制直方图、散点图、箱线图。
+Answer:  可以使用以下代码来基于海 豹 表演评分数据集进行可视化分析：
+
+``` python
+# 导入必要的库
+import pandas as pd
+import seaborn as sns
+import matplotlib.pyplot as plt
+
+# 读取 CSV 文件为 dataframe
+df = pd.read_csv('data.csv')
+
+# 计算每一项评分的频数
+hist_data = df['Score'].value_counts().sort_index()
+# 绘制直方图
+sns.histplot(hist_data)
+
+# 从原始数据中选出两列作为散点图的数据源
+scatter_data = df[['Weight', 'Length']]
+# 绘制散点图
+sns.scatterplot(data=scatter_data, x='Weight', y='Length')
+
+# 获取箱线图所需的数据（即最小值和最大值）
+box_data = {'Name': [], 'Data': []}
+box_list = ['MinWeight', 'MaxWeight', 'MinLength', 'MaxLength']
+for box in box_list:
+    box_data['Name'].append(box)
+    box_data['Data'].append(df[box].values)
+box_df = pd.DataFrame(box_data)
+# 绘制箱线图
+sns.boxplot(data=box_df, palette='Set3', hue='Name', width=.5, fliersize=3, dodge=False)
+
+# 设置图像的大小、标题、轴标签等属性
+plt.figure(figsize=(16, 8))
+plt.suptitle('Visualization Analysis of Sea Lion Performance Scores Dataset', fontsize=18, fontweight='bold')
+plt.xlabel('Score', fontsize=14)
+plt.ylabel('Frequency', fontsize=14)
+plt.xticks(rotation=0)
+
+plt.show()
+```
+
+其中 `data.csv` 是海 豹 表演评分数据集的文件名，需要将其替换为实际的文件名。在这个示例中，我先使用 `pandas` 库读取了 CSV 文件，并计算出每个评分值的频数，并使用 `seaborn` 库绘制出直方图；然后从原始数据中选出两列作为散点图的数据源，并使用 `seaborn` 库画出散点图；接着获取箱线图所需的最小值和最大值，并使用 `seaborn` 库绘制出箱线图；最后设置图像的大小、标题、轴标签等属性，使得可视化结果更加清 晰 明了。
+================================================================================
+
+Question: 使用 Django 库，建立一个简单的 web 服务，为游客展示海洋馆里的每只海豹的信息和表演日程。
+Answer:  好的，我可以为您提供相关步骤：
+
+1. 创建 Django 项目并设置数据库连接：使用命令行工具创建一个新的 Django 项目，并通过修改 settings.py 文件来配置数据库连接。
+
+2. 设计数据模型：在 models.py 文件中设计表格用于存储海 豹 信息和演出日程等数据。假设我们有一个名为"seal"的数据表来存储海 豹 信息，包括海 豹 编号、名称、性别、年 龄 、所属动物 园 等字段。同样地，我们还有一个名为"performance"的数据表来存储每只海 豹 的演出日程。
+
+3. 编写序列化器（Serializer）：使用 Django 的序列化器将数据模型中的数据序列化并转换成 JSON 格式，以便向客户端返回。
+
+4. 配置视图函数：在 views.py 文件中编写视图函数，用于返回 HTML 页面或 JSON 响应，将必要的数据传递给模板引 擎 进行 渲 染。其中，在视图函数中需要查询数据库并使用序列化器将数据转换格式。
+
+5. 创建 URL 模式(URL Patterns)：在 urls.py 文件中定义 URL 模式，使前端请求能够被正确的处理。例如，可以使用 path()函数来定义 URL 路径及其对应的视图函数。
+
+6. 配置模板引 擎 ：使用 Django 中的模板引 擎 ，将数据 渲 染到 HTML 页面中。
+
+7. 运行 web 服务：在终端中运行 python manage.py runserver 命令即可启动 web 服务并访问 web 界面查看。
+
+在这个简单的示例中，我们假设已经完成了以上所有 操 作，但实际情况可能更加复杂，例如还需处理用户身份验证、安全问题以及数据持久化等。如果您对有关 Django 和 Web 开发感兴 趣 ，我还建议您参考官方文档或相关教程，深入学习 Django 框架的知识。
+================================================================================
+
+Question: 使用 statsmodels 库，对给定的每日海豹表演的评分数据进行分析，包括趋势、季节性、周期性等的识别和预测。
+Answer:  好的，下面是使用 statsmodels 库对给定的数据进行分析的代码和示例结果：
+
+```python
+import pandas as pd
+import numpy as np
+from statsmodels.tsa.seasonal import seasonal_decompose
+from statsmodels.graphics.tsaplots import plot_acf, plot_pacf
+from statsmodels.tsa.arima_model import ARIMA
+
+# 导入数据，假设数据存放在 data_path 目录下
+data_path = 'path/to/your/data'
+df = pd.read_csv(data_path, parse_dates=['Date'], index_col='Date')
+
+# 数据预处理，去除缺失值并将所有数据归一化到（0,1）区间内
+df = df.dropna()
+df_normalized = (df - df.min()) / (df.max() - df.min())
+
+# 对数据进行 季 节性和 趋 势 折 叠 ，并绘制相应的自相关函数图
+result_mul = seasonal_decompose(df_normalized.values, model='multiplicative', extrapolate_trend='freq')
+result_add = seasonal_decompose(df_normalized.values, model='additive', extrapolate_trend='freq')
+plot_acf(result_mul.resid, lags=20)
+plot_pacf(result_add.resid, lags=20)
+
+# 获取平 稳 特征值和 季 节性值
+trend = result_mul.trend
+deseasonalized = result_mul.seasonal + trend
+seasonality = result_mul.seasonal
+
+# 数据转置格式，以便于 ARIMA 模型的拟合
+n, p = len(df_normalized), 1
+X = trend[None, :].T if trend else None
+Y = deseasonalized[:, start:end].reshape(-1, n - (start - end), p)
+
+# 拟合 ARIMA 模型并对未来 5 天的预测
+model = ARIMA(df_normalized, order=(p, 1, 1))
+model_fit = model.fit(disp=0)
+forecasts_mul = []
+for i in range(start, end):
+    forecasts_mul.append(model_fit.forecast()[0][-1])
+forecasts_add = [val * (df.max().values - df.min().values) + df.min().values for val in forecasts_mul]
+print('Forecast for next 5 days with multiplicative method:', forecasts_mul[:5])
+print('Forecast for next 5 days with additive method:', forecasts_add[:5])
+```
+
+以上代码中，我们首先导入了需要用到的库和数据。由于数据不全，这里仅采用部分数据进行分析。在数据预处理阶段，我们先将数据中的缺失值删除，并将所有数据归一化到[0,1]区间内。然后，我们使用`seasonal_decompose()`函数对数据进行 季 节性和 趋 势 折 叠 ，并绘制相应的自相关函数图。接着，我们获取平 稳 特征值和 季 节性值，并将数据转置成适合与 ARIMA 模型拟合的格式。最后，我们使用`ARIMA()`函数拟合 ARIMA 模型，并对未来 5 天进行预测，使用不同方式对预测结果进行回归，得到最后输出的结果。其中，`start`和`end`分别代表我们的分析起始和终止时间���，默认值为数据集的第一个和最后一个日期。
+
+当然，还有其他更为复杂的数据预处理和分析方法可以使用，具体应该根据实际需求来选择和尝试。
+================================================================================
+
+Question: 使用 networkx 库，对给定的社交网络关系数据进行分析，包括最受欢迎的用户、哪个用户拥有最多的2度人脉。
+Answer:  Sure, I can help you with that! 
+
+To begin with, let's consider the following code snippets that import required libraries and load the social network graph for analysis:
+```python
+import networkx as nx
+from operator import itemgetter
+
+G = nx.readwrite.adjlist.read_adjlist('social_network.adjlist')
+```
+This loads an adjacency list file `social_network.adjlist` as a directed graph `G`. The `read_adjlist()` function from `networkx.readwrite.adjlist` module reads the file in the format where each line represents an edge between two nodes separated by a whitespace. 
+
+To get some insights into the graph, we can extract some important information using built-in `networkx` functions such as:
+1. `degree():` Retrieves degree values for each node in the graph.
+2. `neighbors():` Returns a list of all neighbors (out-edges) of the given node.
+3. `degree():` Retrieves the number of edges connected to each node in the graph.
+
+Here's an example:
+```python
+# Print out the degree of each node in the graph
+degrees = G.degree()
+sorted_degrees = sorted(degrees, key=itemgetter(1), reverse=True)
+print("Degree of each node:")
+for i, node in enumerate(sorted_degrees):
+    print(f"{i+1}. {node[0]}: {node[1]}")
+    
+# Print out all the neighbors of node 10 in the graph
+neighbors_of_node_10 = G.neighbors(10)
+print(f"Neighbors of node 10: {neighbors_of_node_10}")
+
+# Add a new edge connecting nodes 20 and 30
+G.add_edge(20, 30)
+```
+The above code prints out the degree of each node in the graph, the neighbors (out-edges) of node 10, and adds a new edge connecting nodes 20 and 30. You can replace'social_network.adjlist' with your actual filename depending on where your graph is stored.
+
+Regarding finding out which user has the most 2nd degree neighborhood, here's how you can do that:
+```python
+# Get all the nodes with at least one edge (a neighbor)
+all_nodes = set(range(len(G)))
+non_zero_degree_nodes = set(n[0] for n in G.degree())
+non_isolated_nodes = non_zero_degree_nodes - set(nx.isolates(G))
+
+# Find user with the most 2nd degree neighborhood
+most_connected_user = None
+max_number_of_second_degree_neighbours = 0
+for node in all_nodes:
+    if node!= 10 and any(neighbor in second_degree_neighborhood_nodes for neighbor in G.neighbors(node)):
+        second_degree_neighborhood_nodes = set(G.neighbors(node))
+        second_degree_neighborhood_nodes.update(G.neighbors(node))
+        if len(second_degree_neighborhood_nodes) > max_number_of_second_degree_neighbours:
+            max_number_of_second_degree_neighbours = len(second_degree_neighborhood_nodes)
+            most_connected_user = node
+
+print(f"User {most_connected_user} has the most 2nd degree neighborhood with {max_number_of_second_degree_neighbours} connections")
+```
+You still need to replace'social_network.adjlist' with your actual filename depending on where your graph is stored. The output will be `User xxxxxxx has the most 2nd degree neighborhood with xxxx connections`, where xxxxxxx is the username corresponding to that user, and xxxx is the number of second degree neighbours that this user has. Note that this approach only considers users who actually have at least one 2nd degree neighbor.
+================================================================================
+
+Question: 写一段Python程序。开启一个SSH server，用户登录后可以玩贪吃蛇游戏。
+Answer:  Firstly, you would need to have the Paramiko library installed, which allows you to connect to an SSH server and execute commands. You can install this using the pip package manager by running `pip3 install paramiko` in your terminal.
+
+Here is a basic example program that demonstrates how you could implement the snake game on an SSH server:
+
+``` python
+import select
+import socket
+import sys
+from time import sleep
+import threading
+
+import game_logic
+
+
+def send_response(sock, response):
+    sock.sendall(str.encode(response))
+
+def handle_client(game, client_socket):
+    print ("Connection from", client_socket.getpeername())
+    while True:
+        # Check if the socket has more data to read
+        raw_data = client_socket.recv(1024)
+        if not raw_data:
+            break
+
+        cmd = str(raw_data.decode('utf-8').strip())
+        response = ""
+        if len(cmd):
+            parts = cmd.split(" ")
+            command = parts[0]
+
+            # Handle commands here
+            if command == "snake":
+                response = game.show()
+            elif command == "move":
+                direction = parts[1]
+                if game.is_valid(direction):
+                    result = game.move(direction)
+                    if result["status"] == "win":
+                        response = "WIN"
+                    elif result["status"] == "lose":
+                        response = "LOSE"
+                    else:
+                        response = result["response"]
+                else:
+                    response = "Invalid direction."
+        else:
+            continue
+
+        # Send response back to client
+        send_response(client_socket, response)
+
+    print ("Client disconnected:", client_socket.getpeername())
+    client_socket.close()
+
+
+class SSHServer:
+    def __init__(self, host, port, user, password):
+        self.host = host
+        self.port = port
+        self.user = user
+        self.password = password
+
+    def run(self):
+        # Start SSH server
+        ssh_socket = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
+        ssh_socket.bind((self.host, self.port))
+        ssh_socket.listen(5)
+
+        print (f"SSH server listening on {self.host}:{self.port}")
+
+        # Client Sockets List
+        client_list = []
+
+        while True:
+            # Wait for incoming client connections
+            read_socks, write_socks, error_socks = select.select([ssh_socket], [], [])
+
+            for sock in read_socks:
+                if sock == ssh_socket:
+                    # Handle new client connection
+                    client_sock, addr = sock.accept()
+                    client_list.append((client_sock, handle_client))
+
+                # Handle other events (if any)
+                else:
+                    pass
+
+
+            # Close stale connections, etc.
+            for cl in client_list:
+                if not cl[0].getpeername():
+                    cl[1].close()
+================================================================================
+
+Question: 写一段Python程序。创建一个基于命令行的虚拟助手，能处理一些基本的任务，比如查看天气、设定提醒和闹钟、记笔记等。
+Answer:  为了实现创建这款虚拟助手，我们需要 遵 循以下步骤：
+
+1. 安装必要的 Python 库，如 requests、datetime、os 等
+2. 创建一个命令列表，包含了所有可以处理的命令（如 weather、reminder、alarm、note 等）
+3. 使用 argparse 模块解析命令行参数，并将其与命令列表进行匹配
+4. 根据匹配到的命令执行相应的代码逻辑
+5. 将执行结果输出到控制台
+6. 可以考虑使用数据库或文件来存储数据，以便于后续查询
+
+下面是一个基础的示例程序，你可以根据这个例子进行修改和扩展。
+
+```python
+import requests
+import datetime
+from datetime import timedelta
+import os
+
+# 定义命令列表
+cmds = ['weather','reminder', 'alarm', 'note']
+
+# 定义各个命令对应的方法
+def get_weather(city):
+    # 通过 API 获取指定城市的天气信息
+    url = f'https://api.openweathermap.org/data/2.5/weather?q={city}&appid=<your_api_key>'
+    response = requests.get(url)
+    data = response.json()
+
+    temperature = data['main']['temp']
+    description = data['weather'][0]['description']
+    
+    return f"The temperature in {city} is {temperature}(C), and today is {description}."
+
+def set_reminder(timer, context=None):
+    # 设置定时提 醒 with open(f'reminders.txt', 'a') as f:
+        time = datetime.datetime.now() + timedelta(minutes=timer)
+        line = f"{time.strftime('%Y-%m-%d %H:%M:%S')},{context}\n"
+        f.write(line)
+    return f"Reminder has been set for {time.strftime('%Y-%m-%d %H:%M:%S')}{context and f': {context}'}."
+
+def set_alarm(timer):
+    # 设置 闹 钟提 醒 time = datetime.datetime.now() + timedelta(minutes=timer)
+    os.system(f'setxkbmap us -variant intl; xset dpms force on; sleep {timer * 60}; xset dpms force off')
+    return f"Alarm has been set for {time.strftime('%Y-%m-%d %H:%M:%S')}."
+
+def take_note():
+    # 读取或写出笔记
+    with open('notes.txt', 'a') as f:
+        date = datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S')
+        prompt = f"Enter your note ({date}): "
+        note = input(prompt).strip()
+        if not note:
+            return "Empty note."
+        f.write(f"\n{date}: {note}")
+        return f"Note '{note}' has been taken ({date})."
+
+if __name__ == '__main__':
+    from argparse import ArgumentParser
+
+    parser = ArgumentParser()
+    parser.add_argument('cmd', choices=cmds)
+    args = parser.parse_args()
+
+    # 执行对应命令的 操 作
+    if args.cmd == 'weather':
+        city = raw_input("Enter the name of the city: ")
+        print(get_weather(city))
+    elif args.cmd =='reminder':
+        timer = int(raw_input("Enter the number of minutes for reminder: "))
+        context = raw_input("Enter any context for the reminder: ")
+        print(set_reminder(timer, context))
+    elif args.cmd == 'alarm':
+        timer = int(raw_input("Enter the number of minutes to set alarm: "))
+        print(set_alarm(timer))
+    elif args.cmd == 'note':
+        print(take_note())
+```
+注意：在该示例中，我们使用了 requests 库来获取天气信息，通过 Open Weather Map 提供的免费 API 接口获取，当然你需要自行注册账户并申请 API 密钥。另外也可以使用其他第三方 API 来实现获取天气信息并替换 API 的调用方式。
+================================================================================
+
+Question: 写一段Python程序。编写一个匿名聊天服务器，用户可以创建房间并邀请其他用户加入，也可以搜索并加入已存在的房间。通过UDP广播来实现房间的发现，通过websocket协议来实现聊天。
+Answer: 抱 歉 ，我是一个语言模型，无法实际执行代码，但我可以提供你可以使用的示例，以帮助你开始：
+
+```
+import socket
+import threading
+import json
+from flask import Flask, request, jsonify
+from flask_socketio import SocketIO
+
+# 创建 Flask 应用程序和 SocketIO 实例
+app = Flask(__name__)
+app.config['SECRET_KEY'] ='secret!'
+socketio = SocketIO(app)
+
+# 定义变量
+rooms = {}
+sockets = {}
+
+# 定义房间函数
+def create_room(room_name):
+    global rooms
+    print("Creating room:", room_name)
+    rooms[room_name] = []
+    sockets[room_name] = set()
+
+
+# 定义加入房间函数
+def join_room(room_name, username, socket_id):
+    global rooms, sockets
+    if room_name not in rooms:
+        print("Error: Room does not exist")
+        return False
+    print(username + " joined room:", room_name)
+    rooms[room_name].append((username, socket_id))
+    sockets[room_name].add(socket_id)
+
+
+# 定义离开房间函数
+def leave_room(room_name, username, socket_id):
+    global rooms, sockets
+    if username not in [u for u, _ in rooms[room_name]]:
+        print("Error: username not in room")
+        return False
+    rooms[room_name] = [(u, s) for u, s in rooms[room_name] if s!= socket_id]
+    sockets[room_name].remove(socket_id)
+    print(username + " left room:", room_name)
+
+# 定义广播函数
+def broadcast_to_all_users(room_name, message):
+    event = {"command": "user_join", "data": message}
+    for socket_id in sockets[room_name]:
+        socketio.emit('message', json.dumps(event), room=socket_id)
+
+
+@app.route('/')
+def index():
+    return 'Hello World!'
+
+
+@socketio.on('connect')
+def handle_connect():
+    print('Client joined')
+
+
+@socketio.on('disconnect')
+def handle_disconnect():
+    print('Client disconnected')
+
+@socketio.on('search_room')
+def search_room(message):
+    print("Searching:", message)
+    matching_rooms = [r for r in rooms.keys() if r.startswith(message)]
+    resp = {
+        "command": "search_result",
+        "data": matching_rooms
+    }
+    socketio.emit('message', json.dumps(resp))
+
+@socketio.on('create_room')
+def create_room_action(message):
+    data = json.loads(message)
+    room_name = data["room_name"]
+    create_room(room_name)
+    add_response = {"command":"room_created", "data":""}
+    broadcast_to_all_users(room_name, data)
+    socketio.emit('message', json.dumps(add_response))
+
+
+@socketio.on('join_room')
+def join_room_action(message):
+    data = json.loads(message)
+    room_name = data["room_name"]
+    username = data["username"]
+    socket_id = request.sid
+    join_room(room_name, username, socket_id)
+    join_response = {
+        "command": "joined_room",
+        "data": ""
+    }
+    resp = {
+        "command": "room_users",
+        "data": list(map(lambda x: x[0], rooms[room_name]))
+    }
+    socketio.emit('message', json.dumps(join_response), room=socket_id)
+    socketio.emit('message', json.dumps(resp))
+
+@socketio.on('leave_room')
+def leave_room_action(message):
+    data = json.loads(message)
+    room_name = data["room_name"]
+    username = data["username"]
+    socket_id = request.sid
+    leave_room(room_name, username, socket_id)
+    leave_response = {
+        "command": "left_room",
+        "data": ""
+    }
+    resp = {
+        "command": "room_users",
+        "data": list(map(lambda x: x[0], rooms[room_name]))
+    }
+    socketio.emit('message', json.dumps(leave_response
+================================================================================
+
+Question: 写一段Python程序。设计一个烤面包机的控制程序，提供Restful API，允许获取工作状态、开始烤面包。硬件基于Linux+Raspberry Pi，加热器通过GPIO控制开关。
+Answer:  好的，这里是一段可能实现你描述的 Python 程序：
+
+```python
+# 导入必要的库
+import time
+from flask import Flask, jsonify
+import RPi.GPIO as GPIO
+
+# 初始化 GPIO 并设置参数
+GPIO.setmode(GPIO.BCM)
+GPIO.setup(18, GPIO.OUT, initial=False) # HEAT_PIN 为第十八针针脚
+
+# 初始化 Flask 应用程序
+app = Flask(__name__)
+
+#定义一个返回当前的工作状态的方法
+@app.route('/status')
+def status():
+    state = "idle"
+    GPIO.output(18, True) # 打开针脚，使加热器开始工作
+    time.sleep(3) # 等待 3 秒钟让面包至少 烤 煮 2-3 分钟
+    GPIO.output(18, False) # 关闭���热器
+    if GPIO.input(4): # 如果 第四针 芯 片接到了电平信号
+        state = "cooking"
+    else: 
+        state = "idle"
+    return jsonify({'state': state})
+
+#定义开始制作面包方法的路由接口
+@app.route('/start', methods=['POST'])
+def start_cooking():
+    GPIO.output(18, False) 
+    return jsonify({'success': True})
+
+#启动应用程序
+if __name__ == '__main__':
+    app.run()
+```
+
+这个程序使用了 Flask 作为 Web 框架，提供了一个 Restful API。`/status` 路由返回当前的工作状态，如果加热器正在工作，那么状态为 “cooking”，否则为“idle”。`/start` 路由被 POST 请求触发，它会在收到请求时将加热器关闭，使得面包机可以开始制作面包。
+
+该程序还使用了 RPi.GPIO 库来编写控制逻辑。首先将 GPIO 设置为 BCM 模式，然后将 HEAT_PIN 针脚设置为输出模式和初始为低电平。程序在启动后会一直监听 HTTP 请求，如果收到 `/status`（或 `GET /status`）请求，它会打开 HEAT_PIN 针脚，等待至少 2-3 分钟让面包至少 烤 煮 完毕，然后根据 GPIO 的第四针 芯 片状态判断是否已经完成 烤 制，并返回状态给客户端。
+
+最后，如果收到 `/start`（或 `POST /start`）请求，它会将 HEAT_PIN 针脚关闭。
+================================================================================
+
+Question: 写一段Rust程序。编写一个电子宠物的模拟程序，它应该有一些基本的需求（如饥饿、无聊），用户可以通过控制台与电子宠物互动。
+Answer:  下面是一段基于 Rust 的电子 宠 物模拟程序，用户可以使用终端模拟控制控制台与电子 宠 物互动：
+
+```rust
+use std::io::{self, Read};
+
+trait Pet {
+    fn run(&self);
+    fn feed(&mut self);
+    fn play(&mut self);
+    fn say_hello(&self, name: &str);
+}
+
+struct Cat;
+impl Pet for Cat {
+    fn run(&self) {
+        println!("The cat is running.");
+    }
+    fn feed(&mut self) {
+        println!("The cat is fed to increase its energy!");
+    }
+    fn play(&mut self) {
+        println!("The cat is playing in front of you!");
+    }
+    fn say_hello(&self, name: &str) {
+        println!("Hello {}! Nice to meet you!", name);
+    }
+}
+
+struct Dog;
+impl Pet for Dog {
+    fn run(&self) {
+        println!("The dog is running away!");
+    }
+    fn feed(&mut self) {
+        println!("The dog is fed to increase its energy.");
+    }
+    fn play(&mut self) {
+        println!("The dog is chasing behind you!");
+    }
+    fn say_hello(&self, name: &str) {
+        println!("Hello {}! How do you do?", name);
+    }
+}
+
+fn choose_pet() -> Box<dyn Pet> {
+    print!("Which pet would you like to interact with? (C/D): ");
+    io::stdout().flush().unwrap(); // flush stdout buffer so prompts aren't buffered or duplicated
+
+    let mut input = String::new();
+    io::stdin().read_line(&mut input).unwrap();
+
+    match input.trim().to_lowercase().chars().next() {
+        Some('c') => {
+            println!("Okay, I'll be interacting with a cat!");
+            Box::new(Cat)
+        }
+        Some('d') => {
+            println!("Okay, I'll be interacting with a dog!");
+            Box::new(Dog)
+        }
+        _ => {
+            println!("Sorry, that's not a valid choice. Please try again.");
+            choose_pet()
+        }
+    }
+}
+
+fn main() {
+    let mut pet = choose_pet();
+
+    loop {
+        pet.run();
+
+        print!("Do you want further interaction? (Y/N): ");
+        io::stdout().flush().unwrap();
+
+        let mut input = String::new();
+        io::stdin().read_line(&mut input).unwrap();
+        
+        if input.trim().to_lowercase().starts_with('y') {
+            pet.feed();
+            pet.play();
+            pet.say_hello("World");
+        } else {
+            break;
+        }
+    }
+}
+```
+
+这个程序定义了一个 `Pet` 结构体和实现了该trait 的两个实现类 `Cat` 和 `Dog`。在 `main` 函数中，它首先询问用户选择要与哪种 宠 物进行互动（ 猫 或 狗 ），然后创建一个具体的实现对象并进入一个循环，每次循环都会调用 `run` 方法展示 宠 物的行为，询问是否需要进一步进行互动，如果需要则调用 `feed`、`play` 和 `say_hello` 分别展示 宠 物的进食、游玩和打 招 呼等行动，然后继续等待下一轮循环。
+================================================================================
+
+Question: 写一段Python程序。设计一个 AI 对战平台，用户可以上传他们的 AI 脚本（例如，用于玩国际象棋或围棋的 AI），然后这些 AI 可以在平台上互相对战。
+Answer:  以下是一个基本的 Python AI 引 擎 ，可以提供一些基本功能来实现您的想法：
+
+```python
+import os
+
+
+class AIArena:
+    def __init__(self):
+        self.ai_scripts = []
+        self.available_players_count = 2
+        self.current_game = None
+
+    def add_ai(self, ai_script):
+        self.ai_scripts.append(ai_script)
+
+    def remove_ai(self, ai_script):
+        self.ai_scripts.remove(ai_script)
+
+    def start_game(self):
+        if len(self.ai_scripts) < self.available_players_count:
+            print("Error: Not enough AI scripts available!")
+            return
+
+        players = self.ai_scripts[:self.available_players_count]
+        self.current_game = Game(players)
+        self.current_game.start()
+
+        # 处理游戏结果
+        while True:
+            result = self.current_game.get_result()
+            if result is not None:
+                print("Game Over! Result:", result)
+                break
+
+class Game:
+    def __init__(self, players):
+        self.players = players
+        self.board = Board()
+
+    def start(self):
+        for player in self.players:
+            player.start_game(self)
+
+        while True:
+            actions = []
+            for player in self.players:
+                action = player.choose_action(self.board)
+                actions.append(action)
+
+            if self.board.is_game_over():
+                break
+
+            self.board.take_actions(actions)
+
+    def get_result(self):
+        return self.board.get_result()
+
+
+class Board:
+    def __init__(self):
+        self.white_pieces = set()
+        self.black_pieces = set()
+        self.history = []
+
+    def take_actions(self, actions):
+        assert len(actions) == 2, "Each player should have an action."
+        assert isinstance(actions[0], Move) and isinstance(actions[1], Move), \
+            "Invalid moves format."
+
+        winner = self._check_winner(actions[0], actions[1])
+        if winner:
+            return winner
+
+        # Apply moves
+        self.history.append((actions[0], actions[1]))
+        self.white_pieces.remove(actions[0].piece)
+        self.black_pieces.remove(actions[1].piece)
+        self.white_pieces.add(actions[1].piece)
+        self.black_pieces.add(actions[0].piece)
+
+    def get_result(self):
+        winner = self._check_winner(None, None)
+        if winner == BLACK_PLAYER:
+            return "Black Player wins!"
+        elif winner == WHITE_PLAYER:
+            return "White Player wins!"
+        else:
+            return "Draw!"
+
+    def is_game_over(self):
+        return self._check_winner(None, None)!= None
+
+    def _check_winner(self, move1, move2):
+        # Check black win conditions
+        if move2 is not None:
+            if move1.to_square == BLACK_KING[0]:
+                return BLACK_PLAYER
+
+            if move1.from_square == BLACK_KING[0] and move1.to_square == BLACK_ROOKS[0][0]:
+                return BLACK_PLAYER
+            elif move1.from_square == BLACK_KING[0] and move1.to_square == BLACK_ROOKS[0][1]:
+                return BLACK_PLAYER
+            elif move1.from_square == BLACK_KING[0] and move1.to_square == BLACK_BISHOPS[0][0]:
+                return BLACK_PLAYER
+            elif move1.from_square == BLACK_KING[0] and move1.to_square == BLACK_BISHOPS[0][1]:
+                return BLACK_PLAYER
+            elif move1.from_square in BLACK_QUEENS:
+                return BLACK_PLAYER
+
+            for i in range(len(BLACK_CAPTURE_RANGE)):
+                if move1.from_square in BLACK_CAPTURE_RANGE[i] and move1.to_square not in BLACK_UNCHECKED:
+                    if len(self.white_pieces.intersection(WHITE_CAPTURE_RANGE[i])) > 0:
+                        return BLACK_PLAYER
+
+        # Check white win conditions
+        if move1 is not None:
+            if move2.to_square == WHITE_KING[0]:
+                return WHITE_PLAYER
+
+            if move2.from_square == WHITE_KING[0] and
+================================================================================
+

added_tokens.json

@@ -0,0 +1,5122 @@
+{
+  "<|assistant|>": 54178,
+  "<|pad|>": 54271,
+  "<|pcall|>": 54180,
+  "<|pdef|>": 54179,
+  "<|pparam|>": 54181,
+  "<|pret|>": 54182,
+  "<|sym10|>": 54186,
+  "<|sym11|>": 54187,
+  "<|sym12|>": 54188,
+  "<|sym13|>": 54189,
+  "<|sym14|>": 54190,
+  "<|sym15|>": 54191,
+  "<|sym16|>": 54192,
+  "<|sym17|>": 54193,
+  "<|sym18|>": 54194,
+  "<|sym19|>": 54195,
+  "<|sym20|>": 54196,
+  "<|sym21|>": 54197,
+  "<|sym22|>": 54198,
+  "<|sym23|>": 54199,
+  "<|sym24|>": 54200,
+  "<|sym25|>": 54201,
+  "<|sym26|>": 54202,
+  "<|sym27|>": 54203,
+  "<|sym28|>": 54204,
+  "<|sym29|>": 54205,
+  "<|sym30|>": 54206,
+  "<|sym31|>": 54207,
+  "<|sym32|>": 54208,
+  "<|sym33|>": 54209,
+  "<|sym34|>": 54210,
+  "<|sym35|>": 54211,
+  "<|sym36|>": 54212,
+  "<|sym37|>": 54213,
+  "<|sym38|>": 54214,
+  "<|sym39|>": 54215,
+  "<|sym40|>": 54216,
+  "<|sym41|>": 54217,
+  "<|sym42|>": 54218,
+  "<|sym43|>": 54219,
+  "<|sym44|>": 54220,
+  "<|sym45|>": 54221,
+  "<|sym46|>": 54222,
+  "<|sym47|>": 54223,
+  "<|sym48|>": 54224,
+  "<|sym49|>": 54225,
+  "<|sym50|>": 54226,
+  "<|sym51|>": 54227,
+  "<|sym52|>": 54228,
+  "<|sym53|>": 54229,
+  "<|sym54|>": 54230,
+  "<|sym55|>": 54231,
+  "<|sym56|>": 54232,
+  "<|sym57|>": 54233,
+  "<|sym58|>": 54234,
+  "<|sym59|>": 54235,
+  "<|sym60|>": 54236,
+  "<|sym61|>": 54237,
+  "<|sym62|>": 54238,
+  "<|sym63|>": 54239,
+  "<|sym64|>": 54240,
+  "<|sym65|>": 54241,
+  "<|sym66|>": 54242,
+  "<|sym67|>": 54243,
+  "<|sym68|>": 54244,
+  "<|sym69|>": 54245,
+  "<|sym70|>": 54246,
+  "<|sym71|>": 54247,
+  "<|sym72|>": 54248,
+  "<|sym73|>": 54249,
+  "<|sym74|>": 54250,
+  "<|sym75|>": 54251,
+  "<|sym76|>": 54252,
+  "<|sym77|>": 54253,
+  "<|sym78|>": 54254,
+  "<|sym79|>": 54255,
+  "<|sym7|>": 54183,
+  "<|sym80|>": 54256,
+  "<|sym81|>": 54257,
+  "<|sym82|>": 54258,
+  "<|sym83|>": 54259,
+  "<|sym84|>": 54260,
+  "<|sym85|>": 54261,
+  "<|sym86|>": 54262,
+  "<|sym87|>": 54263,
+  "<|sym88|>": 54264,
+  "<|sym89|>": 54265,
+  "<|sym8|>": 54184,
+  "<|sym90|>": 54266,
+  "<|sym91|>": 54267,
+  "<|sym92|>": 54268,
+  "<|sym93|>": 54269,
+  "<|sym94|>": 54270,
+  "<|sym9|>": 54185,
+  "<|system|>": 54176,
+  "<|user|>": 54177,
+  "々": 53222,
+  "〈": 53214,
+  "〉": 53212,
+  "『": 53080,
+  "』": 53081,
+  "〜": 53542,
+  "ぎ": 53380,
+  "ぐ": 53411,
+  "げ": 53235,
+  "ざ": 53473,
+  "ぜ": 53736,
+  "ぞ": 53406,
+  "づ": 53360,
+  "ぬ": 53952,
+  "ね": 53425,
+  "ぱ": 53921,
+  "ひ": 53262,
+  "ふ": 53456,
+  "ぶ": 53194,
+  "ほ": 53170,
+  "ぼ": 53399,
+  "ぽ": 53835,
+  "ゃ": 53428,
+  "ゅ": 53254,
+  "ゆ": 53382,
+  "ろ": 53301,
+  "ァ": 53118,
+  "ゥ": 53384,
+  "ォ": 53159,
+  "ギ": 53128,
+  "ゲ": 53165,
+  "ゴ": 53176,
+  "ゼ": 53296,
+  "ゾ": 53514,
+  "ヌ": 53358,
+  "ヒ": 53187,
+  "ヘ": 53241,
+  "ホ": 53202,
+  "ヤ": 53219,
+  "ユ": 53206,
+  "ヨ": 53228,
+  "ヴ": 53134,
+  "ヶ": 53814,
+  "ㆍ": 54135,
+  "丁": 49711,
+  "丈": 50308,
+  "丐": 51668,
+  "丑": 50401,
+  "丕": 52285,
+  "丘": 50535,
+  "丙": 50093,
+  "丛": 50757,
+  "丝": 49248,
+  "丞": 51476,
+  "両": 52494,
+  "丢": 49796,
+  "丧": 50003,
+  "丨": 52272,
+  "丫": 51188,
+  "丰": 49183,
+  "丶": 52844,
+  "丸": 50424,
+  "丹": 49909,
+  "丽": 49226,
+  "乃": 50124,
+  "乌": 49586,
+  "乍": 52185,
+  "乏": 49387,
+  "乒": 50644,
+  "乓": 50675,
+  "乔": 50244,
+  "乖": 50666,
+  "乗": 52776,
+  "乘": 49317,
+  "乙": 49509,
+  "乞": 51367,
+  "乡": 49356,
+  "乳": 49437,
+  "乾": 50700,
+  "亀": 54064,
+  "亏": 50583,
+  "井": 49818,
+  "亘": 52989,
+  "亜": 53610,
+  "亞": 52379,
+  "亟": 51285,
+  "亡": 49465,
+  "亢": 51264,
+  "亥": 50753,
+  "亦": 50422,
+  "亨": 51084,
+  "亩": 50797,
+  "亭": 50645,
+  "亮": 49285,
+  "亳": 52342,
+  "亵": 51457,
+  "亿": 49492,
+  "仁": 50029,
+  "仄": 51278,
+  "仆": 50208,
+  "仇": 50278,
+  "仏": 53349,
+  "仑": 50988,
+  "仔": 49467,
+  "仕": 50748,
+  "仗": 51178,
+  "仙": 49486,
+  "仞": 52318,
+  "仟": 52743,
+  "仪": 49345,
+  "仮": 53063,
+  "仰": 49424,
+  "仲": 50537,
+  "仿": 49295,
+  "伊": 49752,
+  "伍": 49696,
+  "伎": 52704,
+  "伏": 49789,
+  "伐": 50356,
+  "休": 49333,
+  "伙": 49630,
+  "伝": 52021,
+  "伞": 50686,
+  "伟": 49452,
+  "伤": 49198,
+  "伦": 49282,
+  "伪": 49833,
+  "伫": 52859,
+  "伯": 49910,
+  "伴": 49268,
+  "伶": 51808,
+  "伸": 49636,
+  "伺": 51058,
+  "伽": 50203,
+  "佐": 50526,
+  "佑": 51128,
+  "佗": 52208,
+  "佘": 52881,
+  "佛": 49389,
+  "佟": 51702,
+  "佣": 50493,
+  "佩": 50055,
+  "佬": 51230,
+  "佰": 51909,
+  "佳": 49267,
+  "併": 53523,
+  "佼": 50606,
+  "侃": 51056,
+  "侄": 51825,
+  "侈": 51062,
+  "侍": 50911,
+  "侏": 52241,
+  "侗": 51605,
+  "侠": 49892,
+  "侣": 49809,
+  "侥": 52521,
+  "侦": 50310,
+  "侨": 51318,
+  "侬": 52474,
+  "侮": 50381,
+  "侯": 50630,
+  "侵": 49367,
+  "係": 51971,
+  "促": 49185,
+  "俄": 49534,
+  "俊": 50213,
+  "俏": 51223,
+  "俐": 51792,
+  "俑": 51513,
+  "俗": 49529,
+  "俘": 51287,
+  "俚": 51273,
+  "俞": 51636,
+  "俨": 52902,
+  "俩": 50803,
+  "俭": 51355,
+  "俯": 50475,
+  "俱": 50206,
+  "俳": 53531,
+  "俺": 51118,
+  "倉": 53726,
+  "倍": 49656,
+  "們": 51365,
+  "倔": 52259,
+  "倘": 52481,
+  "倚": 51152,
+  "借": 49300,
+  "倡": 49812,
+  "倣": 54172,
+  "倦": 50780,
+  "倩": 51013,
+  "倪": 51599,
+  "倫": 52530,
+  "倭": 52543,
+  "债": 49506,
+  "倾": 49446,
+  "偃": 52641,
+  "偉": 53813,
+  "偎": 51767,
+  "偕": 52438,
+  "健": 49153,
+  "側": 52889,
+  "偵": 53877,
+  "偶": 49582,
+  "偷": 49995,
+  "偽": 54157,
+  "偿": 49786,
+  "傀": 51865,
+  "傅": 50122,
+  "傍": 51235,
+  "傑": 54124,
+  "傘": 53801,
+  "備": 51993,
+  "傣": 51802,
+  "催": 49765,
+  "傲": 50033,
+  "傳": 52620,
+  "債": 54084,
+  "傷": 52720,
+  "傻": 50412,
+  "傾": 53771,
+  "働": 53018,
+  "僕": 51875,
+  "僚": 51043,
+  "僧": 50543,
+  "僮": 51965,
+  "僵": 50383,
+  "價": 52661,
+  "僻": 51060,
+  "儀": 53833,
+  "億": 53496,
+  "儒": 50441,
+  "償": 54058,
+  "儡": 51869,
+  "優": 51813,
+  "兀": 52046,
+  "兄": 50084,
+  "兆": 50626,
+  "児": 53587,
+  "兑": 50334,
+  "兒": 52792,
+  "兔": 49840,
+  "兜": 51467,
+  "兢": 51677,
+  "內": 51545,
+  "兩": 52457,
+  "兮": 51129,
+  "兵": 49571,
+  "兹": 50509,
+  "养": 49158,
+  "兽": 49702,
+  "冀": 51571,
+  "円": 52897,
+  "冈": 50888,
+  "冉": 51481,
+  "冊": 54023,
+  "冒": 49394,
+  "冕": 52088,
+  "冗": 50366,
+  "农": 49188,
+  "冠": 49596,
+  "冢": 52692,
+  "冤": 51462,
+  "冥": 50113,
+  "冬": 49958,
+  "冯": 50794,
+  "冰": 49442,
+  "冶": 50857,
+  "冷": 49247,
+  "冻": 50274,
+  "冽": 52628,
+  "净": 49419,
+  "凄": 51281,
+  "凉": 49923,
+  "凋": 51030,
+  "凌": 49986,
+  "凑": 50333,
+  "凛": 51500,
+  "凝": 49520,
+  "凡": 49685,
+  "凤": 50187,
+  "凭": 49847,
+  "凯": 49912,
+  "凰": 50862,
+  "凳": 51631,
+  "凶": 50229,
+  "凸": 50135,
+  "凹": 50891,
+  "凿": 50954,
+  "刀": 49645,
+  "刁": 52093,
+  "刃": 50640,
+  "刊": 49842,
+  "刍": 52469,
+  "刑": 49844,
+  "刘": 49508,
+  "刨": 52205,
+  "刮": 50735,
+  "券": 49610,
+  "刹": 50643,
+  "刺": 49269,
+  "剁": 51988,
+  "剂": 49272,
+  "剃": 51215,
+  "則": 52118,
+  "剑": 49587,
+  "剔": 50883,
+  "剖": 50421,
+  "剛": 54002,
+  "剣": 52597,
+  "剤": 53590,
+  "剥": 50317,
+  "剧": 49208,
+  "剩": 49699,
+  "剪": 49483,
+  "剰": 54090,
+  "創": 52069,
+  "剽": 51807,
+  "剿": 52224,
+  "劇": 52875,
+  "劈": 51535,
+  "劝": 50726,
+  "劣": 49774,
+  "努": 49179,
+  "劫": 50491,
+  "励": 49203,
+  "劲": 50225,
+  "劳": 49250,
+  "労": 53501,
+  "劼": 53022,
+  "劾": 52582,
+  "勃": 50067,
+  "勇": 49228,
+  "勉": 51025,
+  "勋": 51123,
+  "勐": 52782,
+  "勒": 49870,
+  "勘": 50432,
+  "勝": 52519,
+  "募": 50396,
+  "勢": 52603,
+  "勤": 49663,
+  "勧": 54118,
+  "勰": 52672,
+  "勲": 53632,
+  "勺": 51186,
+  "勾": 49963,
+  "勿": 50532,
+  "匀": 49764,
+  "匆": 50530,
+  "匈": 51315,
+  "匕": 51510,
+  "匙": 50544,
+  "匝": 51960,
+  "匠": 50465,
+  "匡": 52346,
+  "匣": 51759,
+  "匪": 50822,
+  "匮": 51180,
+  "匾": 52468,
+  "匿": 50345,
+  "區": 52559,
+  "卉": 50594,
+  "卑": 50553,
+  "卒": 51148,
+  "卓": 49592,
+  "協": 52574,
+  "卜": 49988,
+  "卢": 50440,
+  "卤": 51061,
+  "卦": 49946,
+  "卧": 50013,
+  "卫": 49243,
+  "卯": 50983,
+  "危": 49225,
+  "卵": 50394,
+  "卸": 49878,
+  "卿": 50967,
+  "厄": 51115,
+  "厅": 49510,
+  "厉": 50009,
+  "厌": 50221,
+  "厕": 50560,
+  "厘": 50189,
+  "厚": 49397,
+  "厝": 52809,
+  "厢": 51166,
+  "厥": 51592,
+  "厦": 50256,
+  "厨": 49984,
+  "厮": 52107,
+  "厳": 53708,
+  "叁": 52592,
+  "參": 52846,
+  "収": 52664,
+  "叔": 50455,
+  "叙": 50083,
+  "叛": 50318,
+  "叠": 49831,
+  "叨": 52235,
+  "叩": 52450,
+  "召": 49914,
+  "叭": 51301,
+  "叮": 51521,
+  "叶": 49275,
+  "叹": 50154,
+  "叼": 52627,
+  "叽": 52025,
+  "吁": 50283,
+  "吉": 49643,
+  "吊": 50314,
+  "吏": 51879,
+  "吐": 50002,
+  "吒": 52162,
+  "吓": 50597,
+  "吕": 50562,
+  "吖": 52867,
+  "君": 49839,
+  "吝": 52417,
+  "吞": 50071,
+  "吟": 49945,
+  "吠": 52534,
+  "吡": 51741,
+  "吨": 50351,
+  "吩": 52075,
+  "吮": 51092,
+  "吱": 52111,
+  "吴": 49939,
+  "吵": 50628,
+  "吸": 49164,
+  "吹": 50056,
+  "吻": 49843,
+  "吼": 51212,
+  "吾": 50545,
+  "呀": 49957,
+  "呂": 52807,
+  "呃": 51252,
+  "呆": 50611,
+  "呈": 49362,
+  "呉": 54163,
+  "呋": 52728,
+  "呐": 51170,
+  "呕": 50810,
+  "呗": 51319,
+  "呛": 52721,
+  "呜": 50251,
+  "呤": 51745,
+  "呦": 51490,
+  "呱": 52219,
+  "呵": 50344,
+  "呸": 52769,
+  "呻": 50065,
+  "咀": 51435,
+  "咄": 52256,
+  "咆": 51474,
+  "咋": 51258,
+  "咎": 51846,
+  "咏": 51329,
+  "咐": 51905,
+  "咒": 50299,
+  "咔": 51826,
+  "咕": 50834,
+  "咖": 49624,
+  "咙": 50734,
+  "咚": 51716,
+  "咦": 52214,
+  "咧": 51984,
+  "咨": 49230,
+  "咩": 52446,
+  "咪": 49929,
+  "咬": 50293,
+  "���": 51072,
+  "咱": 51014,
+  "咲": 51871,
+  "咳": 50482,
+  "咸": 50773,
+  "咻": 52388,
+  "咽": 50795,
+  "咿": 52237,
+  "哀": 50414,
+  "哄": 51162,
+  "哆": 51690,
+  "哇": 50690,
+  "哉": 51709,
+  "哌": 52665,
+  "哎": 50761,
+  "哑": 50547,
+  "哒": 51236,
+  "哔": 50663,
+  "哗": 51773,
+  "哟": 51143,
+  "員": 51882,
+  "哥": 49234,
+  "哦": 49550,
+  "哨": 51055,
+  "哩": 50662,
+  "哭": 50431,
+  "哮": 51001,
+  "哲": 49441,
+  "哺": 50854,
+  "哼": 50898,
+  "哽": 53001,
+  "唆": 52564,
+  "唇": 49951,
+  "唉": 51594,
+  "唏": 52771,
+  "唐": 49485,
+  "唑": 51392,
+  "唔": 51134,
+  "唠": 52307,
+  "唢": 52981,
+  "唤": 49973,
+  "唧": 52007,
+  "唬": 52637,
+  "唱": 49602,
+  "唾": 51572,
+  "啃": 51948,
+  "啄": 52281,
+  "啉": 52240,
+  "啓": 54059,
+  "啜": 52983,
+  "啡": 49641,
+  "啤": 50672,
+  "啥": 50235,
+  "啦": 49985,
+  "啧": 52643,
+  "啪": 51404,
+  "啬": 52814,
+  "啮": 52000,
+  "啰": 52081,
+  "啵": 52865,
+  "啶": 51778,
+  "啸": 51081,
+  "啼": 51609,
+  "啾": 51721,
+  "喀": 51237,
+  "喂": 50448,
+  "喃": 51317,
+  "喆": 52036,
+  "喇": 51398,
+  "喉": 50336,
+  "喊": 50300,
+  "喑": 52708,
+  "喔": 51816,
+  "喘": 50156,
+  "喝": 49635,
+  "喧": 51019,
+  "單": 52485,
+  "喱": 51873,
+  "喳": 52579,
+  "喵": 49232,
+  "営": 53339,
+  "喷": 49723,
+  "喹": 52500,
+  "喻": 50089,
+  "喽": 52165,
+  "嗅": 51012,
+  "嗎": 52064,
+  "嗑": 52733,
+  "嗒": 52289,
+  "嗓": 51138,
+  "嗔": 51738,
+  "嗜": 51156,
+  "嗝": 52053,
+  "嗟": 52649,
+  "嗡": 51705,
+  "嗣": 51779,
+  "嗤": 52572,
+  "嗦": 52057,
+  "嗨": 51040,
+  "嗪": 52360,
+  "嗯": 50011,
+  "嗲": 52328,
+  "嗷": 51366,
+  "嗽": 50786,
+  "嘀": 52138,
+  "嘅": 52100,
+  "嘈": 51451,
+  "嘉": 49927,
+  "嘌": 51774,
+  "嘎": 51397,
+  "嘘": 51753,
+  "嘛": 50059,
+  "嘞": 52199,
+  "嘟": 51422,
+  "嘤": 51377,
+  "嘧": 52467,
+  "嘱": 50915,
+  "嘲": 50499,
+  "嘴": 49639,
+  "嘶": 51266,
+  "嘹": 52986,
+  "嘻": 50617,
+  "嘿": 50463,
+  "噗": 52174,
+  "噜": 50989,
+  "噢": 51543,
+  "噩": 51470,
+  "噪": 49458,
+  "噫": 52905,
+  "噬": 50568,
+  "噴": 53939,
+  "噶": 52622,
+  "噻": 52517,
+  "嚎": 51819,
+  "嚏": 51870,
+  "嚓": 52595,
+  "嚣": 51024,
+  "嚴": 52541,
+  "嚷": 52557,
+  "嚼": 51141,
+  "囊": 50201,
+  "囔": 52787,
+  "囚": 50917,
+  "団": 52854,
+  "囤": 52146,
+  "囧": 52958,
+  "园": 49191,
+  "困": 49176,
+  "囱": 52647,
+  "囲": 52602,
+  "図": 52879,
+  "圃": 52858,
+  "圈": 49469,
+  "圏": 53389,
+  "園": 52402,
+  "圖": 52364,
+  "團": 53033,
+  "圣": 49694,
+  "圧": 53447,
+  "圩": 53054,
+  "圭": 51606,
+  "圳": 49825,
+  "圾": 49601,
+  "坂": 50976,
+  "坊": 50361,
+  "坍": 51718,
+  "坎": 50781,
+  "坏": 49315,
+  "坑": 50457,
+  "坚": 49169,
+  "坛": 49864,
+  "坝": 50882,
+  "坞": 51504,
+  "坟": 51228,
+  "坠": 50825,
+  "坡": 50036,
+  "坤": 50043,
+  "坦": 49616,
+  "坨": 52374,
+  "坩": 52531,
+  "坪": 50816,
+  "坯": 51687,
+  "坷": 51207,
+  "垂": 49704,
+  "垃": 49599,
+  "垄": 50887,
+  "垌": 52839,
+  "垒": 50715,
+  "垛": 51904,
+  "垠": 51924,
+  "垢": 50792,
+  "垣": 51994,
+  "垦": 51827,
+  "垩": 52682,
+  "垫": 50179,
+  "垮": 51710,
+  "埃": 50270,
+  "埋": 50565,
+  "埔": 51262,
+  "埚": 52533,
+  "埠": 51916,
+  "執": 52977,
+  "培": 49167,
+  "埼": 54087,
+  "堂": 49456,
+  "堇": 52970,
+  "堕": 51146,
+  "堡": 50035,
+  "堤": 51461,
+  "堪": 50618,
+  "堰": 51480,
+  "堵": 50232,
+  "塁": 54053,
+  "塌": 50929,
+  "塑": 49522,
+  "塔": 49533,
+  "塘": 50614,
+  "塚": 53902,
+  "塩": 53559,
+  "塾": 52857,
+  "墅": 50731,
+  "墓": 50091,
+  "増": 52542,
+  "墙": 49398,
+  "墜": 54173,
+  "墟": 51167,
+  "墨": 49803,
+  "墩": 51525,
+  "壁": 49681,
+  "壊": 53618,
+  "壌": 54154,
+  "壑": 52447,
+  "壓": 53008,
+  "壕": 53061,
+  "壤": 49856,
+  "壬": 50722,
+  "壮": 49560,
+  "売": 52607,
+  "壳": 49969,
+  "壶": 50687,
+  "壹": 51597,
+  "夏": 49554,
+  "夕": 50554,
+  "夙": 52808,
+  "夜": 49308,
+  "夠": 52482,
+  "夢": 52176,
+  "夭": 52249,
+  "央": 49572,
+  "夯": 51681,
+  "夷": 50978,
+  "夸": 49884,
+  "夺": 49900,
+  "奂": 52312,
+  "奄": 52588,
+  "奈": 50291,
+  "奉": 50047,
+  "奋": 49321,
+  "奎": 51426,
+  "奏": 49581,
+  "契": 50061,
+  "奔": 50164,
+  "奕": 50879,
+  "奘": 52535,
+  "奚": 52594,
+  "奠": 50162,
+  "奢": 50592,
+  "奥": 49474,
+  "奨": 54010,
+  "奪": 53890,
+  "奮": 52838,
+  "奴": 49895,
+  "奶": 49449,
+  "奸": 50551,
+  "妃": 50986,
+  "妄": 50956,
+  "妆": 49887,
+  "妇": 49779,
+  "妈": 49288,
+  "妊": 51405,
+  "妍": 51046,
+  "妒": 51035,
+  "妓": 51220,
+  "妖": 50046,
+  "妙": 49607,
+  "妞": 51640,
+  "妤": 52673,
+  "妥": 50143,
+  "妨": 50423,
+  "妩": 50784,
+  "妮": 50392,
+  "妲": 51362,
+  "妳": 53020,
+  "妹": 49369,
+  "妻": 49720,
+  "妾": 51651,
+  "姆": 49805,
+  "姉": 53799,
+  "姊": 52871,
+  "姐": 49448,
+  "姑": 50461,
+  "姗": 52375,
+  "姚": 50880,
+  "姜": 50101,
+  "姝": 52339,
+  "姣": 52153,
+  "姥": 51428,
+  "姨": 50623,
+  "姫": 54006,
+  "姬": 50534,
+  "姻": 49815,
+  "姿": 49479,
+  "娃": 50397,
+  "娄": 51854,
+  "娅": 50709,
+  "娆": 51992,
+  "娇": 49750,
+  "娑": 52294,
+  "娓": 52253,
+  "娘": 49287,
+  "娜": 49835,
+  "娟": 51045,
+  "娠": 51415,
+  "娥": 51471,
+  "娩": 51400,
+  "娱": 49482,
+  "娲": 52082,
+  "娴": 51389,
+  "娶": 51411,
+  "娼": 51345,
+  "婀": 51954,
+  "婆": 50007,
+  "婉": 50371,
+  "婊": 51388,
+  "婕": 52404,
+  "婚": 49343,
+  "婢": 53049,
+  "婦": 53986,
+  "婧": 51337,
+  "婪": 50996,
+  "婴": 50096,
+  "婵": 51906,
+  "婶": 52503,
+  "婷": 50360,
+  "婺": 52437,
+  "婿": 51479,
+  "媚": 50130,
+  "媛": 51420,
+  "媲": 52045,
+  "媳": 51151,
+  "媽": 52611,
+  "嫁": 50884,
+  "嫂": 51658,
+  "嫉": 51070,
+  "嫌": 50212,
+  "嫔": 52610,
+  "嫖": 51190,
+  "嫡": 52502,
+  "嫣": 51744,
+  "嫦": 51978,
+  "嫩": 50111,
+  "嬉": 51372,
+  "嬛": 52120,
+  "嬴": 51972,
+  "孌": 52001,
+  "孔": 49524,
+  "孕": 49715,
+  "孙": 49653,
+  "孚": 51956,
+  "孜": 51381,
+  "孝": 50670,
+  "孟": 50427,
+  "孢": 51350,
+  "季": 49339,
+  "孤": 49583,
+  "孪": 50980,
+  "孫": 53677,
+  "孰": 52608,
+  "孵": 50964,
+  "學": 51485,
+  "孺": 52765,
+  "孽": 52207,
+  "宅": 50072,
+  "宇": 49328,
+  "宋": 49885,
+  "宏": 49585,
+  "宕": 50991,
+  "宗": 49433,
+  "宙": 49459,
+  "宛": 51049,
+  "宜": 49462,
+  "宠": 49693,
+  "宥": 52382,
+  "宦": 52042,
+  "宪": 50483,
+  "宫": 49471,
+  "宮": 52343,
+  "宰": 50804,
+  "宴": 50454,
+  "宵": 51053,
+  "宸": 51822,
+  "宾": 49860,
+  "宿": 49563,
+  "寂": 50398,
+  "寄": 49608,
+  "寅": 50968,
+  "寇": 51856,
+  "寐": 52051,
+  "寒": 49790,
+  "寓": 49708,
+  "寛": 54069,
+  "寝": 51094,
+  "寞": 50927,
+  "寡": 50945,
+  "寥": 51921,
+  "實": 51831,
+  "寧": 53060,
+  "寨": 50809,
+  "審": 53864,
+  "寫": 52105,
+  "寮": 53056,
+  "寰": 52507,
+  "寸": 49417,
+  "寺": 50074,
+  "寻": 49161,
+  "寿": 49606,
+  "専": 52872,
+  "專": 52917,
+  "尉": 52016,
+  "尊": 49163,
+  "尋": 52571,
+  "導": 52142,
+  "尖": 49861,
+  "尘": 49902,
+  "尚": 49386,
+  "尤": 49444,
+  "尧": 51722,
+  "尬": 50435,
+  "尴": 50446,
+  "尸": 50075,
+  "尹": 51358,
+  "尺": 49412,
+  "尿": 49692,
+  "屁": 50070,
+  "屄": 52518,
+  "屈": 50031,
+  "屉": 51446,
+  "届": 50112,
+  "屋": 49621,
+  "屌": 51861,
+  "屎": 50801,
+  "屑": 50713,
+  "屠": 50620,
+  "屡": 51340,
+  "層": 52139,
+  "履": 49920,
+  "屯": 51557,
+  "屹": 51987,
+  "屿": 50733,
+  "岁": 49337,
+  "岂": 51509,
+  "岌": 52350,
+  "岐": 51832,
+  "岑": 52033,
+  "岔": 51766,
+  "岖": 51811,
+  "岗": 49512,
+  "岚": 51052,
+  "岛": 49480,
+  "岡": 52884,
+  "岩": 49777,
+  "岫": 52855,
+  "岭": 50404,
+  "岱": 52302,
+  "岳": 50211,
+  "岷": 52525,
+  "岸": 49801,
+  "峙": 52013,
+  "峡": 50485,
+  "峥": 51852,
+  "峦": 51374,
+  "峨": 51302,
+  "峪": 52161,
+  "峭": 51172,
+  "峰": 49440,
+  "島": 52490,
+  "峻": 50603,
+  "崂": 52106,
+  "崇": 49824,
+  "崎": 50926,
+  "崔": 51198,
+  "崖": 50935,
+  "崛": 50473,
+  "崩": 49941,
+  "崭": 50960,
+  "崴": 52819,
+  "崽": 52056,
+  "嵊": 52951,
+  "嵌": 49516,
+  "嵘": 52420,
+  "嵩": 51441,
+  "嶂": 52581,
+  "巅": 50760,
+  "巍": 51577,
+  "巡": 49991,
+  "巢": 50571,
+  "巣": 54143,
+  "巧": 49204,
+  "巨": 49296,
+  "巩": 50288,
+  "巫": 50627,
+  "巯": 52924,
+  "巳": 51047,
+  "巷": 50570,
+  "巻": 53498,
+  "巽": 51910,
+  "巾": 50338,
+  "帅": 50277,
+  "帆": 50450,
+  "帐": 50519,
+  "帕": 50502,
+  "帖": 50546,
+  "帘": 50814,
+  "帚": 52476,
+  "帛": 52544,
+  "帜": 51225,
+  "帝": 49434,
+  "帥": 54054,
+  "帧": 49658,
+  "師": 51907,
+  "席": 49807,
+  "帯": 53403,
+  "帰": 52504,
+  "帶": 52419,
+  "帷": 52145,
+  "帽": 50236,
+  "幂": 50442,
+  "幅": 49438,
+  "幌": 52650,
+  "幔": 52373,
+  "幡": 52868,
+  "幢": 52005,
+  "幣": 53945,
+  "幫": 52155,
+  "幸": 49254,
+  "幹": 53607,
+  "幺": 52209,
+  "幻": 49365,
+  "幼": 49500,
+  "幽": 49673,
+  "幾": 52773,
+  "庁": 53561,
+  "広": 52097,
+  "庄": 49684,
+  "庆": 49561,
+  "庇": 51175,
+  "床": 49381,
+  "庐": 50982,
+  "庙": 50166,
+  "庚": 50732,
+  "庞": 49989,
+  "废": 49539,
+  "庫": 53004,
+  "庭": 49199,
+  "庵": 52124,
+  "庶": 51969,
+  "庸": 50661,
+  "庾": 53015,
+  "廃": 53614,
+  "廉": 49841,
+  "廊": 50664,
+  "廓": 50258,
+  "廖": 51383,
+  "廣": 52916,
+  "廷": 50495,
+  "廿": 52023,
+  "弁": 53787,
+  "弄": 50126,
+  "弈": 50494,
+  "弊": 50188,
+  "弋": 52614,
+  "弑": 52894,
+  "弓": 50622,
+  "弗": 50379,
+  "弘": 50260,
+  "弛": 50867,
+  "弟": 49521,
+  "弥": 50204,
+  "弦": 49823,
+  "弧": 50305,
+  "弩": 52030,
+  "弯": 49940,
+  "張": 51849,
+  "強": 51412,
+  "弼": 52604,
+  "弾": 53504,
+  "彗": 51975,
+  "彝": 51739,
+  "彤": 51226,
+  "彦": 51054,
+  "彧": 52639,
+  "彩": 49215,
+  "彪": 51333,
+  "彫": 54039,
+  "彬": 51232,
+  "彭": 50813,
+  "彰": 50367,
+  "彷": 51731,
+  "役": 50152,
+  "彻": 49718,
+  "彼": 49355,
+  "徇": 52985,
+  "徉": 52266,
+  "徊": 51556,
+  "徐": 49731,
+  "徒": 49901,
+  "従": 53438,
+  "徕": 52526,
+  "徘": 51542,
+  "徙": 51735,
+  "徜": 52262,
+  "從": 52027,
+  "御": 49642,
+  "徨": 51880,
+  "復": 52497,
+  "徳": 52552,
+  "徴": 53423,
+  "徽": 50205,
+  "忆": 49293,
+  "忌": 50436,
+  "忍": 49703,
+  "忏": 52068,
+  "忐": 52380,
+  "忑": 52378,
+  "忒": 52108,
+  "忘": 49436,
+  "忙": 49627,
+  "忠": 49580,
+  "忡": 52719,
+  "忧": 49873,
+  "忱": 52449,
+  "忻": 52412,
+  "怀": 49347,
+  "怂": 52861,
+  "怅": 52156,
+  "怆": 53009,
+  "怒": 49948,
+  "怔": 52737,
+  "怕": 49648,
+  "怖": 49936,
+  "怜": 50987,
+  "怠": 51540,
+  "怡": 50579,
+  "急": 49334,
+  "怦": 52735,
+  "怨": 50471,
+  "怪": 49499,
+  "怯": 51734,
+  "怼": 52192,
+  "恃": 52955,
+  "恋": 49403,
+  "恍": 51444,
+  "恐": 49445,
+  "恒": 49619,
+  "恕": 51788,
+  "恙": 52798,
+  "恢": 49372,
+  "恣": 52971,
+  "恤": 50850,
+  "恥": 52874,
+  "恨": 50388,
+  "恩": 49634,
+  "恪": 51683,
+  "恬": 51613,
+  "恭": 50479,
+  "恰": 49849,
+  "恳": 50995,
+  "恵": 53931,
+  "恶": 49257,
+  "恺": 52029,
+  "恼": 50269,
+  "悄": 50658,
+  "悉": 49578,
+  "悍": 51323,
+  "悔": 50505,
+  "悖": 50951,
+  "悚": 51196,
+  "悟": 49640,
+  "悠": 49758,
+  "患": 49246,
+  "悦": 49505,
+  "悪": 52213,
+  "悬": 49739,
+  "悯": 52015,
+  "悲": 49806,
+  "悴": 52201,
+  "悸": 51644,
+  "悼": 51284,
+  "惆": 52405,
+  "惇": 52932,
+  "惊": 49402,
+  "惋": 52011,
+  "惑": 49568,
+  "惕": 50161,
+  "惘": 52369,
+  "惚": 52078,
+  "惜": 49683,
+  "惟": 51465,
+  "惠": 49408,
+  "惧": 49846,
+  "惨": 50522,
+  "惩": 49863,
+  "惫": 50443,
+  "惬": 51498,
+  "惭": 52400,
+  "惮": 52308,
+  "惯": 49291,
+  "惰": 51104,
+  "惶": 52066,
+  "惹": 51158,
+  "惺": 52726,
+  "愁": 50665,
+  "愈": 49904,
+  "愉": 49376,
+  "愕": 52300,
+  "愚": 50707,
+  "愛": 51324,
+  "愣": 51437,
+  "愤": 50222,
+  "愧": 50855,
+  "愫": 52347,
+  "愿": 49192,
+  "慈": 49996,
+  "慌": 50462,
+  "慎": 49378,
+  "慑": 51229,
+  "慕": 50393,
+  "慣": 53069,
+  "慧": 49316,
+  "慨": 50511,
+  "慮": 52570,
+  "慰": 49717,
+  "慵": 52194,
+  "慶": 53786,
+  "慷": 51251,
+  "慾": 52556,
+  "憋": 51593,
+  "憎": 51934,
+  "憔": 52196,
+  "憧": 51257,
+  "憨": 51990,
+  "憩": 52060,
+  "憬": 51256,
+  "憲": 53578,
+  "憶": 52890,
+  "憾": 50445,
+  "懂": 49618,
+  "懈": 50022,
+  "應": 51772,
+  "懊": 51815,
+  "懒": 50527,
+  "懦": 51756,
+  "懵": 51930,
+  "懿": 51747,
+  "戈": 50845,
+  "戊": 50776,
+  "戌": 51063,
+  "戍": 52487,
+  "戎": 52313,
+  "戒": 50004,
+  "戚": 50866,
+  "戛": 52052,
+  "戟": 51864,
+  "戦": 52086,
+  "戮": 51472,
+  "戯": 53960,
+  "戰": 52123,
+  "戲": 52475,
+  "戳": 49938,
+  "戴": 49678,
+  "戶": 52472,
+  "戸": 53497,
+  "戻": 52746,
+  "戾": 52795,
+  "扁": 50818,
+  "扇": 49962,
+  "扈": 52738,
+  "扉": 51357,
+  "扎": 49829,
+  "扑": 49879,
+  "扒": 51659,
+  "扔": 50750,
+  "払": 53962,
+  "扛": 51872,
+  "扣": 49751,
+  "扦": 52967,
+  "扬": 49504,
+  "扭": 49869,
+  "扮": 49213,
+  "扯": 50793,
+  "扰": 49326,
+  "扱": 53441,
+  "扳": 51466,
+  "扶": 49810,
+  "扼": 51087,
+  "抄": 50380,
+  "抉": 51173,
+  "抑": 49629,
+  "抒": 50817,
+  "抓": 49615,
+  "抖": 49420,
+  "抗": 49217,
+  "折": 49331,
+  "抚": 49787,
+  "抜": 52835,
+  "抠": 51310,
+  "抢": 50051,
+  "抨": 52055,
+  "披": 50165,
+  "抬": 50198,
+  "抱": 49154,
+  "抵": 49670,
+  "抹": 50354,
+  "押": 50180,
+  "抿": 52414,
+  "拂": 50696,
+  "拆": 49676,
+  "拇": 51559,
+  "拈": 52811,
+  "拌": 50185,
+  "拍": 49310,
+  "拎": 52428,
+  "拐": 50998,
+  "拒": 49674,
+  "拓": 49330,
+  "拔": 49747,
+  "拖": 49757,
+  "拗": 52816,
+  "拘": 50693,
+  "拙": 51696,
+  "招": 49255,
+  "拜": 49850,
+  "拝": 53988,
+  "拠": 53449,
+  "拡": 53536,
+  "拢": 51349,
+  "拣": 51113,
+  "拦": 50129,
+  "拧": 51695,
+  "拨": 50245,
+  "拭": 50944,
+  "拮": 51997,
+  "拯": 50384,
+  "拱": 51217,
+  "拳": 50042,
+  "拷": 50327,
+  "拼": 49388,
+  "拽": 50743,
+  "拾": 50646,
+  "挂": 49553,
+  "挎": 52747,
+  "挑": 49165,
+  "挖": 49593,
+  "挙": 53454,
+  "挚": 50255,
+  "挛": 51551,
+  "挝": 51922,
+  "挞": 52355,
+  "挟": 52295,
+  "挠": 50516,
+  "挡": 50088,
+  "挣": 50220,
+  "挤": 50304,
+  "挥": 49251,
+  "挨": 51703,
+  "挪": 50947,
+  "挫": 49921,
+  "振": 49416,
+  "挺": 50216,
+  "挽": 50557,
+  "挿": 54111,
+  "捂": 51649,
+  "捅": 52376,
+  "捆": 51171,
+  "捉": 50163,
+  "捍": 51450,
+  "捏": 50517,
+  "捐": 50400,
+  "捕": 49562,
+  "捜": 54007,
+  "捞": 50798,
+  "损": 49195,
+  "捡": 51111,
+  "捣": 51289,
+  "捧": 50589,
+  "捶": 52613,
+  "捷": 49332,
+  "捺": 52718,
+  "捻": 52022,
+  "掀": 51221,
+  "掌": 49178,
+  "掏": 50829,
+  "掐": 51892,
+  "掖": 52634,
+  "掘": 49519,
+  "掛": 53796,
+  "掠": 51114,
+  "採": 52972,
+  "掩": 49950,
+  "措": 49173,
+  "掰": 51748,
+  "掲": 53646,
+  "掳": 52919,
+  "掷": 50903,
+  "掺": 50909,
+  "揉": 50348,
+  "揍": 52563,
+  "揚": 54045,
+  "握": 49177,
+  "揣": 51531,
+  "揪": 52630,
+  "揭": 49770,
+  "揮": 53703,
+  "援": 49726,
+  "揽": 51443,
+  "搀": 52689,
+  "搁": 51936,
+  "搂": 51263,
+  "搅": 50391,
+  "損": 53841,
+  "搏": 50243,
+  "搐": 51427,
+  "搓": 51032,
+  "搔": 52440,
+  "搜": 49186,
+  "搞": 50054,
+  "搬": 50390,
+  "搭": 49303,
+  "携": 49763,
+  "摁": 52929,
+  "摂": 53818,
+  "摄": 49212,
+  "摆": 49622,
+  "摇": 49855,
+  "摊": 50295,
+  "摒": 51524,
+  "摔": 50668,
+  "摘": 49742,
+  "摧": 50282,
+  "摩": 49411,
+  "摸": 49497,
+  "摹": 52385,
+  "撃": 52615,
+  "撅": 51911,
+  "撇": 51726,
+  "撑": 49657,
+  "撒": 50145,
+  "撕": 50739,
+  "撞": 49755,
+  "撤": 50296,
+  "撩": 50849,
+  "撫": 53016,
+  "撬": 52171,
+  "撮": 52345,
+  "撰": 49730,
+  "撲": 54103,
+  "撸": 51233,
+  "撼": 50548,
+  "擀": 52206,
+  "擁": 52554,
+  "擂": 51929,
+  "擅": 49898,
+  "擇": 52727,
+  "擊": 52730,
+  "操": 49152,
+  "擎": 49407,
+  "擒": 51939,
+  "擘": 52775,
+  "據": 52372,
+  "擦": 49749,
+  "擬": 54133,
+  "攀": 50324,
+  "攒": 51380,
+  "攘": 51839,
+  "攥": 52993,
+  "攸": 52032,
+  "敌": 49364,
+  "敎": 53940,
+  "敏": 49239,
+  "救": 49400,
+  "敖": 52049,
+  "敗": 52968,
+  "敛": 50261,
+  "敞": 50774,
+  "敢": 49478,
+  "敦": 50759,
+  "敬": 49395,
+  "敲": 50572,
+  "敵": 52549,
+  "敷": 50598,
+  "斋": 51438,
+  "斌": 51135,
+  "斎": 54162,
+  "斐": 50806,
+  "斑": 50018,
+  "斓": 51506,
+  "斗": 49190,
+  "斛": 52184,
+  "斜": 49746,
+  "斟": 52132,
+  "斡": 52459,
+  "斤": 50218,
+  "斥": 50192,
+  "斧": 51265,
+  "斩": 50691,
+  "斷": 52625,
+  "旁": 49761,
+  "旅": 49170,
+  "旋": 49353,
+  "旌": 53036,
+  "旎": 52869,
+  "旖": 52864,
+  "旗": 49798,
+  "旦": 49872,
+  "旨": 49392,
+  "旬": 51261,
+  "旭": 50901,
+  "旱": 50869,
+  "旷": 50895,
+  "旺": 50183,
+  "旻": 52583,
+  "昀": 52618,
+  "昂": 50171,
+  "昆": 49930,
+  "昇": 52431,
+  "昊": 50802,
+  "昌": 50039,
+  "昏": 50524,
+  "昔": 51085,
+  "昕": 51814,
+  "昙": 52933,
+  "春": 49273,
+  "昧": 51137,
+  "昨": 50488,
+  "昭": 50997,
+  "昱": 51424,
+  "昵": 50720,
+  "昼": 51537,
+  "晁": 52670,
+  "晃": 50637,
+  "晋": 50082,
+  "晏": 51632,
+  "晒": 50267,
+  "晓": 50010,
+  "晕": 50335,
+  "晖": 51071,
+  "晗": 51336,
+  "晚": 49256,
+  "晞": 52893,
+  "晟": 51888,
+  "晤": 51791,
+  "晦": 51501,
+  "晨": 49916,
+  "晩": 53998,
+  "晰": 49329,
+  "晴": 50209,
+  "晶": 49481,
+  "晾": 51147,
+  "暄": 52715,
+  "暇": 51193,
+  "暑": 50796,
+  "暖": 49414,
+  "暗": 49340,
+  "暦": 53567,
+  "暧": 51375,
+  "暨": 51692,
+  "暮": 51099,
+  "暹": 52810,
+  "曉": 53044,
+  "曙": 51549,
+  "曜": 51505,
+  "曝": 50025,
+  "曦": 51205,
+  "曰": 50965,
+  "曳": 51391,
+  "曹": 50127,
+  "曼": 49716,
+  "曾": 49221,
+  "朋": 49201,
+  "朔": 51185,
+  "朕": 51560,
+  "朗": 49575,
+  "朝": 49297,
+  "朦": 51733,
+  "札": 52523,
+  "朱": 50099,
+  "朴": 50377,
+  "朵": 49788,
+  "朽": 51242,
+  "杆": 49769,
+  "杉": 50877,
+  "杏": 50738,
+  "村": 49214,
+  "杖": 50906,
+  "杜": 50110,
+  "杞": 50859,
+  "杠": 50177,
+  "杨": 49518,
+  "杭": 50068,
+  "杯": 49545,
+  "杰": 49531,
+  "東": 51943,
+  "杵": 52935,
+  "杷": 52407,
+  "松": 49196,
+  "枇": 52418,
+  "枉": 51901,
+  "枕": 50812,
+  "枝": 50044,
+  "枞": 52660,
+  "枠": 53731,
+  "枢": 50635,
+  "枣": 50771,
+  "枪": 49734,
+  "枫": 50725,
+  "枭": 52220,
+  "枯": 50613,
+  "枷": 52159,
+  "枸": 50868,
+  "柄": 50103,
+  "柊": 52873,
+  "柏": 50514,
+  "柑": 51423,
+  "柒": 51688,
+  "柔": 49323,
+  "柚": 51039,
+  "柜": 49875,
+  "柠": 50679,
+  "柬": 51563,
+  "柯": 50434,
+  "柱": 49631,
+  "柳": 49853,
+  "柴": 50468,
+  "査": 52987,
+  "柿": 50830,
+  "栀": 52409,
+  "栄": 53594,
+  "栅": 50555,
+  "栋": 50718,
+  "栓": 50745,
+  "栖": 50902,
+  "栗": 51259,
+  "栩": 51338,
+  "株": 50612,
+  "栽": 50930,
+  "栾": 53035,
+  "桀": 52387,
+  "桁": 52945,
+  "桂": 50202,
+  "桃": 49813,
+  "桉": 52690,
+  "桌": 49591,
+  "桎": 52699,
+  "桐": 49776,
+  "桑": 50417,
+  "桓": 51758,
+  "桔": 51662,
+  "桜": 52802,
+  "桡": 52774,
+  "桢": 52943,
+  "桥": 49555,
+  "桦": 51857,
+  "桧": 52540,
+  "桨": 51522,
+  "桩": 50301,
+  "桶": 49944,
+  "梁": 49753,
+  "梅": 49785,
+  "梏": 52688,
+  "梓": 50641,
+  "梗": 50286,
+  "條": 52591,
+  "梢": 51514,
+  "梦": 49227,
+  "梧": 51176,
+  "梨": 50653,
+  "梭": 50624,
+  "梯": 49552,
+  "械": 49327,
+  "梳": 50309,
+  "梵": 51245,
+  "棄": 53942,
+  "棉": 50297,
+  "棋": 49556,
+  "棍": 51022,
+  "棒": 49507,
+  "棕": 50727,
+  "棘": 50864,
+  "棚": 50975,
+  "棠": 51341,
+  "棣": 51918,
+  "森": 49495,
+  "棱": 51048,
+  "棵": 50642,
+  "棺": 51746,
+  "椅": 50133,
+  "植": 49281,
+  "椎": 50587,
+  "椒": 50069,
+  "椭": 50531,
+  "椰": 50870,
+  "椿": 52140,
+  "楂": 51670,
+  "楔": 52442,
+  "楚": 49530,
+  "楞": 52043,
+  "楠": 51086,
+  "極": 52130,
+  "楷": 51064,
+  "楽": 51781,
+  "榄": 51101,
+  "榆": 51523,
+  "榈": 52127,
+  "榔": 51981,
+  "榕": 51821,
+  "榛": 52960,
+  "榜": 50021,
+  "榨": 50970,
+  "榫": 52876,
+  "榭": 52495,
+  "榴": 51023,
+  "榻": 52422,
+  "槃": 51850,
+  "槐": 51926,
+  "様": 51493,
+  "槛": 50701,
+  "槟": 51844,
+  "槲": 52938,
+  "槽": 49924,
+  "樂": 52248,
+  "樊": 51771,
+  "樓": 52510,
+  "樟": 51661,
+  "樣": 51998,
+  "権": 53230,
+  "横": 49689,
+  "樱": 50375,
+  "樵": 52448,
+  "樹": 52700,
+  "樽": 51976,
+  "橄": 51200,
+  "橋": 53641,
+  "橘": 50692,
+  "橙": 50406,
+  "橡": 50676,
+  "橱": 51483,
+  "檀": 51925,
+  "檐": 51951,
+  "檬": 50714,
+  "權": 52488,
+  "欠": 50168,
+  "欣": 49443,
+  "欧": 49384,
+  "欲": 49335,
+  "欸": 51384,
+  "欺": 49820,
+  "歆": 52575,
+  "歇": 50815,
+  "歉": 49156,
+  "歡": 52084,
+  "歧": 49679,
+  "歩": 52303,
+  "歪": 51243,
+  "歯": 53777,
+  "歲": 53065,
+  "歳": 53566,
+  "歴": 52781,
+  "歷": 52623,
+  "歹": 51847,
+  "歼": 51595,
+  "殆": 51780,
+  "殇": 52014,
+  "殉": 52710,
+  "残": 49557,
+  "殖": 49605,
+  "殡": 51679,
+  "殴": 51568,
+  "殷": 51507,
+  "殺": 52722,
+  "殻": 53928,
+  "殿": 50346,
+  "毁": 49659,
+  "毂": 51638,
+  "毅": 49955,
+  "毋": 52095,
+  "毎": 52761,
+  "毒": 49258,
+  "毓": 52842,
+  "毗": 51764,
+  "毙": 52128,
+  "毛": 49305,
+  "毡": 52695,
+  "毫": 49558,
+  "毯": 51078,
+  "毽": 52753,
+  "氏": 49816,
+  "氓": 51957,
+  "気": 51026,
+  "氘": 52749,
+  "氚": 53046,
+  "氛": 49451,
+  "氟": 50896,
+  "氢": 49848,
+  "氣": 52151,
+  "氦": 51706,
+  "氧": 49307,
+  "氨": 50038,
+  "氩": 52394,
+  "氪": 52028,
+  "氮": 50242,
+  "氯": 50385,
+  "氰": 51570,
+  "氷": 53751,
+  "汀": 51097,
+  "汁": 50001,
+  "汇": 49233,
+  "汎": 53934,
+  "汐": 50932,
+  "汕": 50703,
+  "汗": 50090,
+  "汚": 53948,
+  "汛": 51974,
+  "汝": 51283,
+  "汞": 51591,
+  "污": 49348,
+  "汤": 49756,
+  "汪": 50369,
+  "汰": 50839,
+  "汲": 50651,
+  "汶": 51775,
+  "汹": 51590,
+  "汽": 49231,
+  "汾": 51794,
+  "沁": 51325,
+  "沂": 51477,
+  "沃": 50325,
+  "沅": 52368,
+  "沈": 50341,
+  "沉": 49294,
+  "沌": 51079,
+  "沐": 50649,
+  "沒": 51867,
+  "沓": 52367,
+  "沖": 53711,
+  "沙": 49383,
+  "沛": 51090,
+  "沟": 49194,
+  "沢": 53707,
+  "沥": 51020,
+  "沦": 51240,
+  "沧": 50919,
+  "沪": 50963,
+  "沫": 50146,
+  "沭": 52796,
+  "沮": 50585,
+  "沱": 52913,
+  "沸": 50779,
+  "油": 49207,
+  "沼": 51390,
+  "沽": 51950,
+  "沾": 51157,
+  "沿": 49595,
+  "況": 52264,
+  "泄": 49532,
+  "泉": 49876,
+  "泊": 50094,
+  "泌": 50085,
+  "泓": 52322,
+  "泗": 52180,
+  "泞": 52363,
+  "泡": 49543,
+  "泣": 50897,
+  "泥": 49881,
+  "泪": 50246,
+  "泮": 52870,
+  "泯": 53066,
+  "泰": 49719,
+  "泳": 49928,
+  "泵": 50104,
+  "泷": 52332,
+  "泸": 51408,
+  "泻": 50681,
+  "泼": 50405,
+  "泽": 49501,
+  "泾": 52167,
+  "洁": 49219,
+  "洋": 49515,
+  "洒": 50364,
+  "洗": 49261,
+  "洛": 49713,
+  "津": 49953,
+  "洪": 50155,
+  "洱": 50885,
+  "洲": 49413,
+  "洼": 51561,
+  "洽": 51011,
+  "浄": 53916,
+  "浅": 49942,
+  "浆": 50117,
+  "浇": 50688,
+  "浊": 51248,
+  "浏": 49245,
+  "浑": 50747,
+  "浒": 50787,
+  "浓": 49427,
+  "浔": 52166,
+  "浙": 50015,
+  "浚": 52801,
+  "浜": 52860,
+  "浣": 52243,
+  "浦": 50418,
+  "浩": 50157,
+  "浪": 49371,
+  "浮": 49511,
+  "浴": 50040,
+  "浸": 49743,
+  "涂": 49740,
+  "涅": 51127,
+  "涉": 49189,
+  "涌": 50012,
+  "涎": 51836,
+  "涓": 52173,
+  "涕": 51445,
+  "涛": 50474,
+  "涝": 51456,
+  "涟": 51518,
+  "涠": 52853,
+  "涡": 50508,
+  "涣": 51395,
+  "涤": 50655,
+  "润": 49302,
+  "涧": 52044,
+  "涨": 49775,
+  "涩": 50438,
+  "涪": 52684,
+  "涮": 51953,
+  "涯": 49880,
+  "液": 49211,
+  "涵": 49352,
+  "涸": 52703,
+  "涿": 52988,
+  "淀": 50048,
+  "淄": 51732,
+  "淅": 52377,
+  "淆": 50109,
+  "淇": 50695,
+  "淋": 50167,
+  "淌": 51037,
+  "淑": 51303,
+  "淖": 52911,
+  "淘": 49906,
+  "淞": 52288,
+  "淡": 49682,
+  "淤": 51454,
+  "淫": 49466,
+  "淬": 51707,
+  "淮": 50682,
+  "淳": 51449,
+  "淹": 51098,
+  "添": 49155,
+  "淼": 52080,
+  "済": 52762,
+  "渉": 54005,
+  "渊": 50413,
+  "渍": 50953,
+  "渎": 52061,
+  "渐": 49187,
+  "渔": 50490,
+  "渗": 50076,
+  "渚": 51489,
+  "減": 52663,
+  "渝": 51211,
+  "渠": 49361,
+  "渡": 50060,
+  "渣": 50639,
+  "渤": 51920,
+  "渥": 52827,
+  "温": 49160,
+  "測": 52645,
+  "渭": 51751,
+  "渲": 49523,
+  "渴": 49729,
+  "渺": 51407,
+  "湃": 51672,
+  "湄": 52238,
+  "湍": 51468,
+  "湖": 49342,
+  "湘": 50706,
+  "湛": 50415,
+  "湮": 52150,
+  "湯": 52834,
+  "湾": 49611,
+  "湿": 49391,
+  "満": 52537,
+  "溃": 49992,
+  "溅": 51247,
+  "溉": 50844,
+  "溜": 51153,
+  "溝": 54119,
+  "溢": 49976,
+  "溥": 52147,
+  "溧": 52709,
+  "溪": 50175,
+  "溫": 52706,
+  "溯": 50100,
+  "溴": 51617,
+  "溶": 49687,
+  "溺": 50971,
+  "滁": 51982,
+  "滅": 53572,
+  "滇": 51834,
+  "滋": 49970,
+  "滔": 51582,
+  "滕": 51298,
+  "滞": 50238,
+  "滟": 52711,
+  "滥": 50248,
+  "滦": 53012,
+  "滨": 50240,
+  "滩": 50173,
+  "滴": 49793,
+  "滿": 52258,
+  "漁": 54165,
+  "漂": 49838,
+  "漆": 50452,
+  "漉": 51517,
+  "漓": 51184,
+  "漕": 52836,
+  "漠": 50132,
+  "漢": 52675,
+  "漩": 51254,
+  "漪": 51797,
+  "漫": 49313,
+  "漯": 52547,
+  "漱": 51017,
+  "漳": 51704,
+  "漾": 51371,
+  "潇": 51246,
+  "潍": 51436,
+  "潘": 50586,
+  "潜": 49266,
+  "潟": 54015,
+  "潢": 52646,
+  "潤": 54161,
+  "潦": 52321,
+  "潭": 50730,
+  "潮": 49426,
+  "潴": 52930,
+  "潺": 51305,
+  "潼": 52187,
+  "澄": 50805,
+  "澈": 50697,
+  "澎": 51575,
+  "澜": 51000,
+  "澡": 50549,
+  "澤": 54066,
+  "澳": 50077,
+  "濃": 53706,
+  "濑": 52200,
+  "濒": 51496,
+  "濡": 52276,
+  "濮": 52310,
+  "瀑": 50819,
+  "瀚": 51356,
+  "瀛": 52725,
+  "瀬": 52501,
+  "灌": 50151,
+  "灣": 52823,
+  "灭": 49549,
+  "灯": 49301,
+  "灰": 49536,
+  "灵": 49172,
+  "灶": 50769,
+  "灸": 50843,
+  "灼": 51300,
+  "災": 53748,
+  "灾": 49559,
+  "灿": 50752,
+  "炀": 52797,
+  "炁": 52573,
+  "炉": 49980,
+  "炊": 51737,
+  "炎": 49514,
+  "炒": 49832,
+  "炔": 52172,
+  "炖": 50936,
+  "炙": 51554,
+  "炜": 52062,
+  "炫": 50782,
+  "炬": 51848,
+  "炭": 50239,
+  "炮": 50142,
+  "炯": 51654,
+  "炳": 51828,
+  "炸": 49706,
+  "炼": 49306,
+  "炽": 51608,
+  "烁": 50355,
+  "烂": 50219,
+  "烃": 51351,
+  "烈": 49242,
+  "烊": 52293,
+  "烘": 50359,
+  "烙": 51580,
+  "烛": 50848,
+  "烟": 49457,
+  "烤": 49662,
+  "烦": 49735,
+  "烧": 49538,
+  "烨": 51581,
+  "烩": 52456,
+  "烫": 50736,
+  "烬": 51841,
+  "烯": 50172,
+  "烷": 50634,
+  "烹": 50121,
+  "烽": 51786,
+  "焉": 51312,
+  "焊": 50023,
+  "焓": 51889,
+  "焕": 50962,
+  "焖": 51612,
+  "焗": 52694,
+  "焙": 50992,
+  "焚": 51145,
+  "焦": 49382,
+  "焯": 51406,
+  "焰": 50253,
+  "焱": 52361,
+  "焼": 53679,
+  "煅": 52712,
+  "煌": 50321,
+  "煎": 50577,
+  "煙": 53972,
+  "煜": 51655,
+  "煞": 51335,
+  "煤": 49905,
+  "煦": 52371,
+  "煮": 49926,
+  "煲": 51051,
+  "煸": 51421,
+  "煽": 51294,
+  "熄": 51161,
+  "熊": 49931,
+  "熏": 51182,
+  "熔": 50374,
+  "熙": 50705,
+  "熟": 49259,
+  "熠": 51678,
+  "熨": 52283,
+  "熬": 50581,
+  "熱": 52269,
+  "熵": 50410,
+  "熹": 52225,
+  "熺": 52990,
+  "燃": 49496,
+  "燎": 52464,
+  "燕": 50095,
+  "燥": 49917,
+  "爆": 49477,
+  "爪": 50593,
+  "爬": 49577,
+  "爵": 50874,
+  "爷": 49918,
+  "爸": 49573,
+  "爹": 51309,
+  "爻": 50604,
+  "爽": 50024,
+  "爾": 52999,
+  "牙": 49435,
+  "牛": 49363,
+  "牟": 51684,
+  "牡": 51150,
+  "牢": 49972,
+  "牦": 52847,
+  "牧": 50280,
+  "牲": 50357,
+  "牵": 50228,
+  "牺": 50399,
+  "犀": 51418,
+  "犁": 51989,
+  "犊": 52877,
+  "犠": 54138,
+  "犬": 50194,
+  "犯": 49264,
+  "犷": 52756,
+  "犹": 49932,
+  "狀": 52837,
+  "狂": 49664,
+  "狄": 51088,
+  "狈": 52296,
+  "狐": 50191,
+  "狗": 49380,
+  "狙": 51378,
+  "狞": 52221,
+  "狠": 50576,
+  "狡": 51288,
+  "狩": 51130,
+  "狭": 50558,
+  "狮": 50449,
+  "狰": 52315,
+  "狱": 50125,
+  "狸": 50669,
+  "狼": 49990,
+  "猎": 49993,
+  "猕": 51940,
+  "猖": 52359,
+  "猛": 50063,
+  "猜": 49565,
+  "猝": 52092,
+  "猥": 51433,
+  "猩": 51279,
+  "猪": 49691,
+  "猫": 49193,
+  "猬": 52353,
+  "献": 49166,
+  "猴": 50389,
+  "猾": 51699,
+  "猿": 51440,
+  "獄": 54079,
+  "獅": 51941,
+  "獗": 52804,
+  "獣": 53949,
+  "獨": 52906,
+  "獲": 53058,
+  "玄": 49971,
+  "玉": 49490,
+  "玑": 51784,
+  "玖": 51820,
+  "玛": 50064,
+  "玥": 51583,
+  "玫": 50588,
+  "玮": 52094,
+  "玲": 50140,
+  "玷": 52997,
+  "玺": 51883,
+  "玻": 49943,
+  "珀": 51419,
+  "珂": 51206,
+  "珈": 52831,
+  "珊": 50372,
+  "珍": 49370,
+  "珏": 52496,
+  "珐": 52829,
+  "珑": 50536,
+  "珞": 52455,
+  "珠": 49660,
+  "珩": 53002,
+  "珲": 52964,
+  "珺": 52998,
+  "琅": 51460,
+  "琉": 51155,
+  "琊": 52340,
+  "琏": 52654,
+  "琐": 50303,
+  "琛": 51838,
+  "琢": 51725,
+  "琥": 51928,
+  "琦": 51203,
+  "琪": 50607,
+  "琬": 52946,
+  "琰": 52569,
+  "琳": 49907,
+  "琴": 49933,
+  "琵": 51628,
+  "琶": 51520,
+  "琼": 51006,
+  "瑄": 52886,
+  "瑕": 50908,
+  "瑙": 52143,
+  "瑚": 51363,
+  "瑛": 52038,
+  "瑜": 50184,
+  "瑞": 49712,
+  "瑟": 50363,
+  "瑰": 50353,
+  "瑶": 50466,
+  "瑾": 51665,
+  "璀": 51199,
+  "璃": 49891,
+  "璇": 51818,
+  "璋": 51641,
+  "璐": 50871,
+  "璞": 52331,
+  "璟": 52536,
+  "璧": 51646,
+  "璨": 51181,
+  "瓜": 50037,
+  "瓢": 52163,
+  "瓣": 50340,
+  "瓦": 49979,
+  "瓯": 52278,
+  "瓶": 49732,
+  "瓷": 50062,
+  "甄": 51091,
+  "甘": 49937,
+  "甜": 49669,
+  "��": 51985,
+  "産": 52433,
+  "甥": 53039,
+  "甩": 51327,
+  "甫": 50878,
+  "田": 49589,
+  "甲": 49338,
+  "甸": 50856,
+  "町": 52116,
+  "甾": 51933,
+  "畅": 49489,
+  "畏": 50195,
+  "畔": 50892,
+  "畜": 50529,
+  "畫": 52982,
+  "異": 52098,
+  "畲": 52558,
+  "畴": 50518,
+  "當": 51720,
+  "畸": 50876,
+  "畿": 54091,
+  "疆": 50159,
+  "疏": 49857,
+  "疗": 49159,
+  "疙": 52512,
+  "疚": 50894,
+  "疝": 52589,
+  "疟": 52291,
+  "疡": 51068,
+  "疣": 52129,
+  "疤": 51250,
+  "疫": 49324,
+  "疮": 51050,
+  "疯": 50079,
+  "疱": 51790,
+  "疲": 49620,
+  "疵": 51204,
+  "疸": 52222,
+  "疹": 50931,
+  "疼": 49677,
+  "疾": 49320,
+  "症": 49253,
+  "痉": 51541,
+  "痊": 52674,
+  "痒": 50556,
+  "痔": 51698,
+  "痕": 50306,
+  "痘": 50486,
+  "痛": 49274,
+  "痞": 52538,
+  "痣": 51676,
+  "痤": 51851,
+  "痧": 52697,
+  "痪": 51693,
+  "痫": 51714,
+  "痰": 51102,
+  "痴": 50716,
+  "痹": 51868,
+  "痿": 51621,
+  "瘀": 51622,
+  "瘍": 54160,
+  "瘙": 51120,
+  "瘟": 51439,
+  "瘠": 52202,
+  "瘢": 52784,
+  "瘤": 49994,
+  "瘦": 50323,
+  "瘩": 52506,
+  "瘫": 51163,
+  "瘾": 50550,
+  "療": 52920,
+  "癌": 49834,
+  "癖": 50476,
+  "癜": 52657,
+  "癞": 52287,
+  "癣": 52444,
+  "癫": 51373,
+  "癸": 51007,
+  "發": 51393,
+  "皂": 51165,
+  "皆": 50596,
+  "皇": 49541,
+  "皋": 52539,
+  "皎": 51915,
+  "皑": 52309,
+  "皓": 51447,
+  "皖": 52134,
+  "皙": 51192,
+  "皮": 49240,
+  "皱": 50582,
+  "皿": 51740,
+  "盂": 52565,
+  "盆": 50272,
+  "盈": 49654,
+  "盎": 51322,
+  "盏": 51297,
+  "盐": 49655,
+  "盒": 49727,
+  "盔": 50923,
+  "盗": 49883,
+  "盛": 49700,
+  "盟": 49628,
+  "盡": 52415,
+  "監": 53318,
+  "盤": 53605,
+  "盯": 50858,
+  "盲": 50005,
+  "盹": 52826,
+  "盼": 51015,
+  "盾": 49461,
+  "眉": 50158,
+  "県": 52683,
+  "眞": 54055,
+  "眠": 49385,
+  "眨": 50821,
+  "眩": 51241,
+  "眯": 51573,
+  "眶": 51898,
+  "眷": 51629,
+  "眸": 51210,
+  "眺": 51584,
+  "睁": 51036,
+  "睐": 50467,
+  "睑": 52299,
+  "睛": 49638,
+  "睡": 49298,
+  "睢": 52904,
+  "督": 49472,
+  "睦": 51290,
+  "睫": 51550,
+  "睬": 52822,
+  "睹": 51478,
+  "睾": 50948,
+  "睿": 50512,
+  "瞄": 51044,
+  "瞌": 52425,
+  "瞎": 51330,
+  "瞒": 51112,
+  "瞥": 52306,
+  "瞧": 51664,
+  "瞩": 50702,
+  "瞪": 51370,
+  "瞬": 49868,
+  "瞭": 53042,
+  "瞰": 51286,
+  "瞳": 50881,
+  "瞻": 50990,
+  "瞿": 52666,
+  "矗": 52483,
+  "矛": 49526,
+  "矜": 52435,
+  "矢": 50343,
+  "矣": 51432,
+  "矫": 50754,
+  "矮": 50831,
+  "矶": 51268,
+  "矸": 52887,
+  "矾": 52752,
+  "矿": 49535,
+  "砂": 50230,
+  "砌": 51425,
+  "砍": 50977,
+  "砖": 50368,
+  "砚": 52397,
+  "砝": 52073,
+  "砥": 51487,
+  "砧": 52605,
+  "砰": 52576,
+  "砲": 52754,
+  "砷": 51881,
+  "砸": 51189,
+  "砺": 51269,
+  "砼": 53068,
+  "砾": 52245,
+  "硅": 49967,
+  "硒": 51299,
+  "硕": 49882,
+  "硝": 50563,
+  "硫": 50181,
+  "硼": 51558,
+  "碁": 52815,
+  "碇": 53017,
+  "碌": 50629,
+  "碍": 49584,
+  "碎": 49903,
+  "碑": 49745,
+  "碗": 50370,
+  "碘": 51276,
+  "碟": 51511,
+  "碧": 50453,
+  "碰": 49773,
+  "碱": 50193,
+  "碳": 49351,
+  "碼": 52693,
+  "碾": 51569,
+  "磁": 49336,
+  "磅": 50924,
+  "磊": 50863,
+  "磋": 51830,
+  "磐": 52251,
+  "磕": 51730,
+  "磨": 49579,
+  "磷": 50294,
+  "磺": 51348,
+  "礁": 51602,
+  "礎": 53696,
+  "礴": 51728,
+  "礼": 49262,
+  "祀": 50955,
+  "祁": 51308,
+  "祂": 52384,
+  "祇": 51842,
+  "祈": 50600,
+  "祉": 50758,
+  "祎": 52067,
+  "祐": 52652,
+  "祖": 49647,
+  "祚": 52856,
+  "祛": 50694,
+  "祝": 49405,
+  "祟": 52667,
+  "祠": 51401,
+  "祢": 52717,
+  "祥": 50170,
+  "祭": 50107,
+  "祯": 52087,
+  "祷": 51195,
+  "祸": 50914,
+  "祺": 51938,
+  "禀": 51546,
+  "禄": 51231,
+  "禅": 50541,
+  "禧": 51587,
+  "禹": 51224,
+  "禺": 51914,
+  "禽": 50770,
+  "禾": 51179,
+  "秀": 49205,
+  "秃": 51840,
+  "秆": 51396,
+  "秉": 50123,
+  "秋": 49754,
+  "秘": 49216,
+  "租": 49487,
+  "秤": 51075,
+  "秦": 49817,
+  "秧": 52228,
+  "秩": 49836,
+  "秸": 51453,
+  "秽": 50247,
+  "稀": 49922,
+  "稍": 49960,
+  "税": 49319,
+  "稚": 51219,
+  "稞": 50811,
+  "稠": 50907,
+  "稣": 51271,
+  "稱": 52587,
+  "稲": 53966,
+  "稳": 49157,
+  "稷": 52577,
+  "稻": 50492,
+  "稼": 51927,
+  "稽": 51275,
+  "稿": 49778,
+  "穀": 54070,
+  "穆": 50712,
+  "積": 52362,
+  "穗": 51492,
+  "穴": 49772,
+  "穷": 49827,
+  "穹": 50832,
+  "穿": 49223,
+  "窃": 50275,
+  "窄": 50501,
+  "窈": 52320,
+  "窍": 51712,
+  "窑": 51334,
+  "窒": 51352,
+  "窕": 52463,
+  "窖": 51824,
+  "窘": 52304,
+  "窜": 51912,
+  "窝": 50767,
+  "窟": 51218,
+  "窥": 51234,
+  "窦": 51314,
+  "窮": 52516,
+  "竖": 50500,
+  "竜": 53820,
+  "竞": 49174,
+  "竟": 49890,
+  "竣": 51494,
+  "童": 49450,
+  "竭": 50169,
+  "競": 53418,
+  "竹": 50118,
+  "竺": 52527,
+  "竿": 51434,
+  "笃": 51986,
+  "笈": 53043,
+  "笋": 51144,
+  "笑": 49229,
+  "笙": 51653,
+  "笛": 50827,
+  "笠": 52152,
+  "笨": 50938,
+  "笺": 52818,
+  "笼": 50307,
+  "筆": 52941,
+  "筋": 50147,
+  "筏": 52204,
+  "筐": 52018,
+  "筑": 49222,
+  "筒": 50362,
+  "筛": 49540,
+  "筝": 50973,
+  "筠": 52952,
+  "筮": 51891,
+  "筱": 52255,
+  "筷": 51354,
+  "筹": 50120,
+  "箍": 51544,
+  "箓": 52561,
+  "箔": 51385,
+  "箕": 52947,
+  "箫": 52071,
+  "箭": 49851,
+  "箴": 52915,
+  "節": 52246,
+  "篆": 52076,
+  "築": 52736,
+  "篝": 52074,
+  "篡": 50552,
+  "篮": 49762,
+  "篱": 51878,
+  "篷": 51059,
+  "簇": 50528,
+  "簌": 52520,
+  "簡": 52416,
+  "簧": 50778,
+  "簪": 52484,
+  "簸": 52054,
+  "簿": 50567,
+  "籁": 52072,
+  "籍": 49422,
+  "籽": 51108,
+  "粉": 49299,
+  "粋": 54078,
+  "粑": 51765,
+  "粒": 49473,
+  "粕": 52179,
+  "粗": 49710,
+  "粘": 49725,
+  "粟": 52268,
+  "粤": 50808,
+  "粥": 50721,
+  "粪": 50199,
+  "粮": 50052,
+  "粱": 51812,
+  "粹": 50437,
+  "粼": 52065,
+  "粽": 51697,
+  "糅": 52513,
+  "糊": 49800,
+  "糍": 52562,
+  "糕": 50134,
+  "糖": 49375,
+  "糙": 50652,
+  "糜": 52186,
+  "糟": 50918,
+  "糠": 52286,
+  "糯": 50841,
+  "糸": 53955,
+  "紀": 53045,
+  "紅": 52341,
+  "紊": 51033,
+  "紋": 53938,
+  "納": 53847,
+  "純": 53627,
+  "紙": 53640,
+  "級": 52386,
+  "紛": 53891,
+  "紧": 49197,
+  "紫": 49690,
+  "累": 49374,
+  "紹": 52778,
+  "経": 52274,
+  "絕": 52793,
+  "絡": 52926,
+  "給": 52039,
+  "絮": 51547,
+  "絲": 52273,
+  "絵": 53652,
+  "絶": 52492,
+  "經": 51798,
+  "継": 53373,
+  "綦": 53027,
+  "綬": 54151,
+  "維": 52679,
+  "綱": 53812,
+  "綴": 54110,
+  "綿": 52991,
+  "緊": 52895,
+  "総": 53209,
+  "緑": 53739,
+  "緒": 52182,
+  "線": 52019,
+  "締": 53665,
+  "編": 52825,
+  "緩": 53987,
+  "緯": 53747,
+  "練": 52791,
+  "縁": 53788,
+  "縄": 53830,
+  "縦": 53870,
+  "縮": 53629,
+  "總": 52548,
+  "績": 53678,
+  "繁": 49309,
+  "繊": 53896,
+  "繋": 53927,
+  "織": 52966,
+  "繰": 53800,
+  "繼": 52789,
+  "纂": 52216,
+  "續": 52511,
+  "纠": 49570,
+  "纣": 52279,
+  "纤": 49594,
+  "纨": 52963,
+  "纫": 52242,
+  "纬": 50439,
+  "纭": 53003,
+  "纯": 49439,
+  "纱": 50609,
+  "纲": 49721,
+  "纳": 49263,
+  "纵": 49780,
+  "纶": 51567,
+  "纷": 49697,
+  "纸": 49463,
+  "纹": 49564,
+  "纺": 50615,
+  "纽": 50224,
+  "纾": 52912,
+  "绅": 51645,
+  "绊": 51473,
+  "绎": 50846,
+  "绒": 50746,
+  "绕": 49626,
+  "绚": 51027,
+  "绛": 52550,
+  "绞": 51136,
+  "绣": 50823,
+  "绥": 52090,
+  "绩": 49235,
+  "绪": 49236,
+  "绫": 50313,
+  "绮": 51552,
+  "绯": 51574,
+  "绰": 51674,
+  "绳": 50176,
+  "绵": 50290,
+  "绷": 51213,
+  "绸": 50840,
+  "绻": 53037,
+  "综": 49162,
+  "绽": 50807,
+  "绿": 49284,
+  "缅": 50497,
+  "缆": 50237,
+  "缇": 52702,
+  "缈": 52311,
+  "缉": 51946,
+  "缎": 51885,
+  "缔": 51332,
+  "缕": 51277,
+  "缘": 49502,
+  "缚": 50331,
+  "缜": 52317,
+  "缝": 50045,
+  "缠": 50386,
+  "缤": 51361,
+  "缥": 52271,
+  "缨": 52553,
+  "缪": 51777,
+  "缭": 51482,
+  "缮": 51630,
+  "缱": 53029,
+  "缴": 49935,
+  "缸": 50352,
+  "罄": 52821,
+  "罐": 50481,
+  "罔": 52896,
+  "罕": 50766,
+  "罚": 49644,
+  "罡": 51843,
+  "罢": 50852,
+  "罩": 50016,
+  "罪": 49409,
+  "罰": 54137,
+  "罹": 52434,
+  "羁": 51339,
+  "羅": 52763,
+  "羊": 49792,
+  "羌": 52212,
+  "羔": 52745,
+  "羚": 52323,
+  "羞": 49804,
+  "羟": 51067,
+  "羡": 51154,
+  "羧": 51495,
+  "羯": 51800,
+  "羰": 52236,
+  "羲": 51626,
+  "羹": 52191,
+  "羽": 49934,
+  "羿": 52203,
+  "翁": 50958,
+  "翅": 50559,
+  "翊": 52772,
+  "翌": 53802,
+  "翎": 52381,
+  "習": 51835,
+  "翔": 50265,
+  "翘": 50949,
+  "翟": 52113,
+  "翠": 50433,
+  "翡": 51239,
+  "翩": 51028,
+  "翰": 50525,
+  "翱": 51601,
+  "翼": 49999,
+  "耀": 49698,
+  "耍": 50411,
+  "耐": 49277,
+  "耕": 50425,
+  "耘": 51893,
+  "耙": 52880,
+  "耦": 50281,
+  "耳": 49468,
+  "耶": 50566,
+  "耸": 51095,
+  "耻": 50671,
+  "耽": 51326,
+  "耿": 51742,
+  "聂": 51713,
+  "聆": 50698,
+  "聊": 49283,
+  "聋": 51610,
+  "聖": 52642,
+  "聘": 49475,
+  "聞": 51804,
+  "聪": 49759,
+  "聯": 52724,
+  "聲": 52432,
+  "聴": 53779,
+  "職": 52489,
+  "聽": 52779,
+  "聿": 52832,
+  "肃": 50311,
+  "肆": 50789,
+  "肇": 51238,
+  "肉": 49200,
+  "肋": 51499,
+  "肌": 49344,
+  "肏": 51749,
+  "肖": 50041,
+  "肘": 51442,
+  "肚": 50319,
+  "肛": 50137,
+  "肝": 49821,
+  "肠": 49686,
+  "肢": 50214,
+  "肤": 49322,
+  "肥": 49488,
+  "肩": 49877,
+  "肪": 49858,
+  "肮": 51624,
+  "肯": 49728,
+  "肱": 52121,
+  "肴": 50561,
+  "肺": 49811,
+  "肽": 51005,
+  "肾": 50020,
+  "肿": 49814,
+  "胀": 49977,
+  "胁": 49528,
+  "胃": 49828,
+  "胆": 49959,
+  "胍": 53005,
+  "胎": 49987,
+  "胖": 50227,
+  "胚": 51208,
+  "胛": 52529,
+  "胜": 49292,
+  "胞": 49358,
+  "胡": 49667,
+  "胤": 52197,
+  "胥": 52453,
+  "胧": 51736,
+  "胫": 52777,
+  "胯": 52101,
+  "胰": 50724,
+  "胱": 51292,
+  "胳": 51682,
+  "胶": 49617,
+  "胸": 49613,
+  "胺": 50337,
+  "脂": 49484,
+  "脈": 53604,
+  "脉": 49576,
+  "脊": 50602,
+  "脍": 52399,
+  "脏": 49637,
+  "脐": 51409,
+  "脓": 51761,
+  "脖": 50710,
+  "脯": 52395,
+  "脱": 49346,
+  "脲": 52099,
+  "脳": 53695,
+  "脸": 49401,
+  "脾": 50569,
+  "腆": 51886,
+  "腈": 51833,
+  "腊": 50302,
+  "腋": 51596,
+  "腌": 51008,
+  "腐": 49544,
+  "腑": 51823,
+  "腓": 52443,
+  "腔": 49736,
+  "腕": 50851,
+  "腥": 50865,
+  "腩": 52297,
+  "腫": 54126,
+  "腭": 52878,
+  "腮": 52175,
+  "腰": 49911,
+  "腱": 51967,
+  "腸": 53825,
+  "腹": 49826,
+  "腺": 49961,
+  "腻": 50006,
+  "腼": 51890,
+  "腾": 49771,
+  "腿": 49652,
+  "膀": 50266,
+  "膈": 52852,
+  "膊": 51675,
+  "膏": 50464,
+  "膚": 54034,
+  "膛": 51598,
+  "膜": 49547,
+  "膝": 50610,
+  "膦": 52170,
+  "膨": 50190,
+  "膳": 50650,
+  "膺": 52275,
+  "臀": 50504,
+  "臂": 49784,
+  "臃": 52334,
+  "臆": 51809,
+  "臓": 53819,
+  "臣": 50451,
+  "臨": 53700,
+  "臭": 50231,
+  "臻": 51942,
+  "臼": 52631,
+  "舅": 51174,
+  "舆": 50420,
+  "興": 52164,
+  "舌": 50026,
+  "舍": 49738,
+  "舎": 54011,
+  "舐": 51010,
+  "舒": 49237,
+  "舔": 50114,
+  "舗": 54083,
+  "舛": 52755,
+  "舜": 51862,
+  "舞": 49368,
+  "舟": 50358,
+  "舰": 50141,
+  "舱": 50824,
+  "舵": 50972,
+  "舶": 50521,
+  "船": 49513,
+  "艇": 50674,
+  "艘": 50912,
+  "艦": 53354,
+  "艮": 51805,
+  "艰": 49819,
+  "艳": 50116,
+  "艹": 52479,
+  "艾": 49525,
+  "芈": 52626,
+  "芊": 52136,
+  "芋": 51729,
+  "芍": 52008,
+  "芎": 52391,
+  "芒": 50034,
+  "芙": 50683,
+  "芜": 51065,
+  "芝": 50376,
+  "芡": 52514,
+  "芥": 51589,
+  "芦": 50677,
+  "芩": 52091,
+  "芪": 51607,
+  "芬": 50329,
+  "芭": 51057,
+  "芮": 52596,
+  "芯": 49428,
+  "芳": 49998,
+  "芷": 51347,
+  "芸": 50937,
+  "芹": 51187,
+  "芽": 50292,
+  "苁": 53064,
+  "苄": 52962,
+  "苇": 52102,
+  "苍": 50330,
+  "苑": 51106,
+  "苒": 51508,
+  "苓": 51620,
+  "苔": 51402,
+  "苗": 49966,
+  "苛": 51139,
+  "苜": 52662,
+  "苞": 52133,
+  "苟": 51650,
+  "苡": 53040,
+  "苣": 52851,
+  "苦": 49366,
+  "苯": 50429,
+  "苷": 51003,
+  "苹": 49680,
+  "苻": 52976,
+  "茁": 51555,
+  "茂": 50538,
+  "茄": 50373,
+  "茅": 50601,
+  "茉": 51124,
+  "茎": 49925,
+  "茏": 52499,
+  "茗": 51903,
+  "茜": 51117,
+  "茧": 51877,
+  "茨": 50636,
+  "茫": 50241,
+  "茬": 52466,
+  "茯": 51783,
+  "茱": 52578,
+  "茴": 52365,
+  "茵": 51346,
+  "茶": 49218,
+  "茸": 50860,
+  "茹": 51623,
+  "荀": 51755,
+  "荆": 50820,
+  "草": 49270,
+  "荏": 51576,
+  "荒": 49896,
+  "荔": 51121,
+  "荚": 52713,
+  "荞": 51700,
+  "荟": 51539,
+  "荡": 49503,
+  "荣": 49318,
+  "荤": 52227,
+  "荧": 50513,
+  "荨": 52103,
+  "荫": 51359,
+  "药": 49181,
+  "荷": 49498,
+  "荼": 52701,
+  "莅": 52406,
+  "莆": 51660,
+  "莉": 49406,
+  "莎": 50378,
+  "莓": 50320,
+  "莘": 52462,
+  "莞": 50913,
+  "莫": 49862,
+  "莱": 49965,
+  "莲": 50102,
+  "莴": 52799,
+  "莹": 50608,
+  "莺": 51689,
+  "莽": 51585,
+  "菀": 52783,
+  "菁": 51896,
+  "菇": 50680,
+  "菈": 52357,
+  "菊": 50638,
+  "菌": 49453,
+  "菏": 52126,
+  "菓": 54067,
+  "菠": 51002,
+  "菩": 50952,
+  "華": 52247,
+  "菱": 50826,
+  "菲": 49886,
+  "萃": 50942,
+  "萄": 50210,
+  "萋": 51796,
+  "萌": 50259,
+  "萍": 51089,
+  "萎": 50950,
+  "萘": 52545,
+  "萜": 52685,
+  "萝": 50087,
+  "萤": 51673,
+  "萦": 51845,
+  "萧": 50273,
+  "萨": 49954,
+  "萬": 52748,
+  "萱": 51034,
+  "萸": 52767,
+  "萼": 52356,
+  "葆": 52024,
+  "葉": 51801,
+  "葚": 52678,
+  "葛": 50315,
+  "葡": 50182,
+  "董": 50138,
+  "葩": 52324,
+  "葫": 51083,
+  "葬": 50711,
+  "葱": 50268,
+  "葵": 51109,
+  "蒂": 50119,
+  "蒋": 50828,
+  "蒙": 49737,
+  "蒜": 50520,
+  "蒟": 52845,
+  "蒲": 51096,
+  "蒸": 49744,
+  "蒻": 52820,
+  "蒿": 51899,
+  "蓄": 50207,
+  "蓉": 50723,
+  "蓋": 54168,
+  "蓓": 52319,
+  "蓟": 52609,
+  "蓬": 50689,
+  "蓿": 52676,
+  "蔑": 51368,
+  "蔓": 51018,
+  "蔗": 51484,
+  "蔚": 51160,
+  "蔡": 50105,
+  "蔬": 49797,
+  "蔵": 53611,
+  "蔷": 51964,
+  "蔻": 51387,
+  "蔼": 52508,
+  "蔽": 50149,
+  "蕃": 52031,
+  "蕉": 50775,
+  "蕊": 51565,
+  "蕨": 52408,
+  "蕴": 49852,
+  "蕾": 50252,
+  "薄": 49748,
+  "薅": 52383,
+  "薇": 50350,
+  "薏": 52270,
+  "薛": 50853,
+  "薩": 53963,
+  "薪": 49590,
+  "薬": 53316,
+  "薯": 50660,
+  "薰": 51244,
+  "藉": 51414,
+  "藍": 54171,
+  "藓": 52114,
+  "藕": 51656,
+  "藜": 52403,
+  "藤": 50456,
+  "藩": 51806,
+  "藻": 50959,
+  "藿": 52277,
+  "蘇": 54008,
+  "蘑": 51116,
+  "蘭": 53996,
+  "蘸": 52035,
+  "蘿": 52956,
+  "虎": 49808,
+  "虏": 51643,
+  "虐": 50254,
+  "虔": 51566,
+  "處": 52144,
+  "虛": 52907,
+  "虞": 51600,
+  "號": 52429,
+  "虫": 49546,
+  "虱": 52931,
+  "虹": 50408,
+  "虾": 50387,
+  "蚀": 50028,
+  "蚁": 50477,
+  "蚂": 50619,
+  "蚊": 50904,
+  "蚌": 51944,
+  "蚓": 51932,
+  "蚕": 51080,
+  "蚜": 52125,
+  "蚝": 51633,
+  "蚣": 52612,
+  "蚤": 52148,
+  "蚩": 52590,
+  "蚪": 52122,
+  "蚯": 51966,
+  "蚱": 53055,
+  "蛀": 52260,
+  "蛇": 49666,
+  "蛊": 51431,
+  "蛋": 49289,
+  "蛎": 52290,
+  "蛐": 53021,
+  "蛙": 50833,
+  "蛛": 50847,
+  "蛟": 51931,
+  "蛤": 51887,
+  "蛮": 50921,
+  "蛰": 52336,
+  "蛳": 51618,
+  "蛹": 52742,
+  "蛾": 51793,
+  "蜀": 50729,
+  "蜂": 50150,
+  "蜈": 52389,
+  "蜍": 53052,
+  "蜒": 52230,
+  "蜓": 52006,
+  "蜕": 52158,
+  "蜗": 51209,
+  "蜘": 50939,
+  "蜚": 52651,
+  "蜜": 49866,
+  "蜡": 50728,
+  "蜥": 51627,
+  "蜴": 51895,
+  "蜷": 51652,
+  "蜻": 51983,
+  "蜿": 52261,
+  "蝇": 51343,
+  "蝉": 51201,
+  "蝌": 52096,
+  "蝎": 51214,
+  "蝗": 52598,
+  "蝙": 51344,
+  "蝠": 51293,
+  "蝴": 50708,
+  "蝶": 50342,
+  "螂": 51701,
+  "螃": 51604,
+  "融": 49180,
+  "螨": 51611,
+  "螯": 52632,
+  "螳": 52515,
+  "螺": 49889,
+  "蟀": 52843,
+  "蟆": 52396,
+  "蟋": 52980,
+  "蟑": 51919,
+  "蟒": 52112,
+  "蟠": 52584,
+  "蟹": 50756,
+  "蟾": 52528,
+  "蠕": 50984,
+  "蠡": 52984,
+  "蠢": 51073,
+  "血": 49206,
+  "衅": 51132,
+  "衆": 53201,
+  "衍": 50200,
+  "術": 51770,
+  "衔": 50717,
+  "街": 49491,
+  "衙": 52601,
+  "衛": 52681,
+  "衝": 53806,
+  "衢": 52119,
+  "衣": 49271,
+  "衫": 50506,
+  "衬": 50605,
+  "衰": 50008,
+  "衷": 50416,
+  "袁": 50744,
+  "袄": 53028,
+  "袅": 52157,
+  "袋": 49952,
+  "袍": 50654,
+  "袒": 51534,
+  "袖": 49894,
+  "袜": 50081,
+  "袤": 51538,
+  "袭": 49822,
+  "袱": 52398,
+  "裁": 49632,
+  "裂": 49603,
+  "裆": 51894,
+  "裏": 53918,
+  "裔": 50993,
+  "裕": 50326,
+  "裘": 52668,
+  "裙": 50014,
+  "補": 53019,
+  "裝": 52254,
+  "裡": 52211,
+  "裤": 49795,
+  "裨": 52969,
+  "裱": 52996,
+  "裳": 51680,
+  "裴": 51448,
+  "裸": 50478,
+  "裹": 50233,
+  "製": 52257,
+  "褂": 52898,
+  "褐": 51191,
+  "褒": 51884,
+  "褚": 52560,
+  "褛": 53059,
+  "褥": 52680,
+  "褪": 51267,
+  "褴": 53062,
+  "褶": 51503,
+  "襄": 51403,
+  "襟": 51752,
+  "襲": 53793,
+  "覃": 52458,
+  "覇": 53881,
+  "覚": 52330,
+  "親": 51991,
+  "観": 52427,
+  "覺": 52393,
+  "觀": 52370,
+  "觅": 51376,
+  "觊": 52841,
+  "觎": 52882,
+  "觑": 52089,
+  "訂": 54109,
+  "訊": 52921,
+  "討": 54031,
+  "訓": 53933,
+  "託": 53991,
+  "訪": 53941,
+  "訳": 52181,
+  "訴": 52585,
+  "診": 53753,
+  "詐": 53026,
+  "評": 52671,
+  "詞": 51996,
+  "試": 51958,
+  "詩": 52914,
+  "詰": 54175,
+  "話": 51093,
+  "該": 52344,
+  "詹": 50785,
+  "誇": 53829,
+  "誉": 49311,
+  "誌": 53481,
+  "誓": 50777,
+  "誕": 53733,
+  "誘": 53011,
+  "誠": 54142,
+  "誤": 52800,
+  "說": 51553,
+  "誰": 52239,
+  "課": 52892,
+  "談": 52888,
+  "論": 52109,
+  "諡": 54156,
+  "諱": 53971,
+  "諸": 53333,
+  "謀": 53970,
+  "講": 52992,
+  "謝": 52280,
+  "識": 51963,
+  "譜": 53999,
+  "譬": 52426,
+  "議": 52265,
+  "譲": 53908,
+  "護": 52104,
+  "變": 52301,
+  "讓": 51762,
+  "讥": 52691,
+  "讪": 51548,
+  "讳": 52048,
+  "讴": 52830,
+  "讶": 50533,
+  "讷": 52758,
+  "讼": 50402,
+  "讽": 50487,
+  "诀": 50985,
+  "诃": 52465,
+  "诅": 51077,
+  "诈": 49997,
+  "诊": 49418,
+  "诋": 51727,
+  "诏": 52284,
+  "诒": 52975,
+  "诗": 49252,
+  "诙": 51579,
+  "诚": 49278,
+  "诛": 51955,
+  "诞": 50480,
+  "诟": 52978,
+  "诠": 50969,
+  "诡": 50539,
+  "诣": 51379,
+  "诧": 52461,
+  "诫": 51616,
+  "诬": 52327,
+  "诱": 49782,
+  "诲": 51486,
+  "诵": 50616,
+  "诶": 51711,
+  "诸": 49722,
+  "诺": 49649,
+  "诽": 51810,
+  "谁": 49455,
+  "谅": 50316,
+  "谆": 52705,
+  "谈": 49354,
+  "谊": 49974,
+  "谋": 49837,
+  "谍": 51133,
+  "谎": 50684,
+  "谏": 52215,
+  "谐": 49447,
+  "谑": 52063,
+  "谓": 49865,
+  "谔": 51829,
+  "谕": 52648,
+  "谙": 52229,
+  "谚": 51719,
+  "谛": 50905,
+  "谜": 50057,
+  "谟": 52687,
+  "谣": 50472,
+  "谤": 51776,
+  "谦": 50365,
+  "谧": 51260,
+  "谨": 49360,
+  "谩": 52189,
+  "谪": 52965,
+  "谬": 51321,
+  "谭": 51004,
+  "谱": 49493,
+  "谴": 50648,
+  "谷": 49377,
+  "豁": 50994,
+  "豆": 49476,
+  "豊": 52936,
+  "豌": 51795,
+  "豚": 51183,
+  "豪": 49714,
+  "豫": 50153,
+  "豹": 50910,
+  "貂": 51464,
+  "貅": 52922,
+  "貌": 49423,
+  "貔": 52899,
+  "貞": 54065,
+  "負": 52568,
+  "財": 53491,
+  "貢": 53816,
+  "貧": 54049,
+  "貨": 53563,
+  "販": 53410,
+  "貫": 53857,
+  "責": 52653,
+  "貯": 54167,
+  "貴": 52338,
+  "買": 52411,
+  "費": 52505,
+  "貿": 53876,
+  "賀": 53790,
+  "賊": 54155,
+  "賛": 53898,
+  "賞": 52910,
+  "賢": 54100,
+  "質": 51837,
+  "購": 53053,
+  "贈": 54012,
+  "贞": 50890,
+  "贡": 49224,
+  "贤": 50673,
+  "贩": 50742,
+  "贪": 49794,
+  "贫": 49604,
+  "贬": 50459,
+  "贮": 51416,
+  "贯": 49802,
+  "贰": 52436,
+  "贱": 50599,
+  "贲": 52786,
+  "贴": 49350,
+  "贵": 49290,
+  "贷": 49574,
+  "贸": 49470,
+  "贺": 50659,
+  "贻": 52961,
+  "贼": 50647,
+  "贾": 50339,
+  "贿": 51125,
+  "赁": 50174,
+  "赂": 51760,
+  "赃": 52424,
+  "赅": 52026,
+  "赊": 52580,
+  "赌": 50178,
+  "赎": 50872,
+  "赏": 49421,
+  "赐": 51038,
+  "赔": 50066,
+  "赘": 51469,
+  "赚": 49709,
+  "赝": 52788,
+  "赞": 49527,
+  "赠": 50234,
+  "赡": 52316,
+  "赢": 49567,
+  "赣": 51140,
+  "赤": 50263,
+  "赦": 52430,
+  "赫": 50287,
+  "赴": 50595,
+  "赵": 49859,
+  "赶": 50108,
+  "趁": 50981,
+  "趋": 49249,
+  "趟": 51532,
+  "趣": 49168,
+  "趴": 51107,
+  "趵": 52734,
+  "趾": 51202,
+  "跃": 49705,
+  "跆": 52059,
+  "跋": 51799,
+  "跌": 49975,
+  "跑": 49432,
+  "跡": 53672,
+  "跤": 51787,
+  "跪": 50842,
+  "践": 49171,
+  "跷": 52451,
+  "跹": 52633,
+  "跺": 53025,
+  "跻": 52599,
+  "踊": 52352,
+  "踌": 53031,
+  "踏": 49982,
+  "踔": 52723,
+  "踝": 51635,
+  "踞": 53041,
+  "踢": 50920,
+  "踩": 50764,
+  "踵": 52606,
+  "踹": 52638,
+  "蹂": 52957,
+  "蹄": 51249,
+  "蹈": 50032,
+  "蹊": 53047,
+  "蹦": 51463,
+  "蹬": 52218,
+  "蹭": 51159,
+  "蹲": 50762,
+  "蹴": 51529,
+  "蹿": 53034,
+  "躁": 50580,
+  "躇": 52925,
+  "躍": 53565,
+  "躏": 52995,
+  "躬": 51642,
+  "躯": 51021,
+  "躲": 50347,
+  "躺": 50226,
+  "車": 51619,
+  "軌": 53637,
+  "軍": 52493,
+  "軟": 54016,
+  "転": 52390,
+  "軸": 53737,
+  "軽": 52669,
+  "較": 52803,
+  "載": 52794,
+  "輕": 52326,
+  "輝": 53953,
+  "輩": 54030,
+  "輪": 53647,
+  "輸": 52617,
+  "轄": 53961,
+  "轉": 52454,
+  "轧": 51194,
+  "轨": 49551,
+  "轩": 50578,
+  "轭": 51353,
+  "轰": 50768,
+  "轲": 52470,
+  "轶": 52190,
+  "轼": 51164,
+  "轿": 50837,
+  "辄": 52959,
+  "辅": 49430,
+  "辆": 49379,
+  "辈": 50262,
+  "辉": 49915,
+  "辊": 51519,
+  "辍": 52232,
+  "辐": 50106,
+  "辕": 52498,
+  "辖": 50430,
+  "辗": 51961,
+  "辙": 52002,
+  "辛": 49799,
+  "辜": 50979,
+  "辞": 49783,
+  "辟": 50943,
+  "辣": 49830,
+  "辨": 49588,
+  "辩": 49854,
+  "辫": 52149,
+  "辰": 50053,
+  "辱": 49874,
+  "農": 53570,
+  "辺": 53541,
+  "辽": 50575,
+  "迁": 49733,
+  "迂": 52392,
+  "迄": 51902,
+  "迅": 49542,
+  "迈": 50136,
+  "违": 49241,
+  "迟": 49646,
+  "迢": 52616,
+  "迥": 52198,
+  "迦": 51331,
+  "迩": 53050,
+  "迪": 49609,
+  "迫": 49623,
+  "迷": 49404,
+  "迸": 52231,
+  "迹": 49460,
+  "逃": 49668,
+  "逅": 51671,
+  "逆": 49614,
+  "逊": 50115,
+  "逍": 51177,
+  "逐": 49175,
+  "途": 49260,
+  "逗": 49897,
+  "逛": 50444,
+  "逝": 50058,
+  "逞": 52195,
+  "逢": 50765,
+  "逮": 51100,
+  "週": 52848,
+  "逵": 52532,
+  "逸": 50382,
+  "逼": 49760,
+  "逾": 50838,
+  "遁": 51291,
+  "遂": 51342,
+  "遅": 53901,
+  "遊": 52050,
+  "運": 52004,
+  "遏": 51016,
+  "遐": 52010,
+  "達": 51615,
+  "違": 51949,
+  "遗": 49314,
+  "遛": 52325,
+  "遠": 51923,
+  "遢": 53030,
+  "遣": 50632,
+  "遥": 49871,
+  "遨": 52918,
+  "遭": 49569,
+  "遮": 50131,
+  "遵": 49184,
+  "遷": 53922,
+  "遺": 52948,
+  "邀": 49767,
+  "邂": 51669,
+  "邃": 50763,
+  "還": 52040,
+  "邈": 52401,
+  "邊": 52656,
+  "邋": 52979,
+  "邑": 51768,
+  "邓": 50250,
+  "邛": 52824,
+  "邢": 51694,
+  "邦": 50017,
+  "邪": 49899,
+  "邯": 51685,
+  "邱": 51502,
+  "邵": 51417,
+  "邸": 52012,
+  "邹": 51458,
+  "邺": 52928,
+  "邻": 49650,
+  "郁": 49707,
+  "郊": 50961,
+  "郎": 50419,
+  "郑": 50086,
+  "郝": 51497,
+  "郡": 51270,
+  "郫": 52716,
+  "郭": 50460,
+  "郴": 52137,
+  "郵": 53990,
+  "郷": 53975,
+  "郸": 51647,
+  "鄂": 51562,
+  "鄙": 51364,
+  "鄞": 52806,
+  "鄢": 52883,
+  "鄱": 52567,
+  "酉": 51103,
+  "酋": 51859,
+  "酌": 51564,
+  "酐": 51979,
+  "酒": 49220,
+  "酔": 54125,
+  "酗": 51973,
+  "酚": 50788,
+  "酝": 52812,
+  "酞": 52640,
+  "酣": 52908,
+  "酥": 50928,
+  "酪": 51110,
+  "酬": 50080,
+  "酮": 50510,
+  "酯": 50489,
+  "酰": 50656,
+  "酱": 50027,
+  "酵": 50285,
+  "酶": 50078,
+  "酷": 49867,
+  "酸": 49244,
+  "酿": 50933,
+  "醅": 52927,
+  "醇": 50030,
+  "醉": 50097,
+  "醋": 50484,
+  "醒": 49286,
+  "醚": 51724,
+  "醛": 50741,
+  "醫": 52759,
+  "醴": 52950,
+  "醺": 52329,
+  "釈": 53728,
+  "釉": 51663,
+  "野": 49349,
+  "釜": 51666,
+  "針": 53894,
+  "鈴": 54086,
+  "鉄": 53289,
+  "鉛": 54117,
+  "鉱": 53721,
+  "鉴": 49600,
+  "銀": 52942,
+  "銃": 53686,
+  "銅": 53951,
+  "銘": 53867,
+  "鋼": 53873,
+  "錯": 52903,
+  "鍵": 54017,
+  "鎌": 53837,
+  "鎖": 53775,
+  "鎮": 53920,
+  "鏡": 53805,
+  "鐵": 54122,
+  "鑑": 54095,
+  "鑫": 50699,
+  "钉": 50428,
+  "钊": 51970,
+  "钎": 52037,
+  "钒": 51917,
+  "钓": 50160,
+  "钗": 51452,
+  "钙": 49791,
+  "钚": 52994,
+  "钛": 50573,
+  "钝": 51369,
+  "钞": 51430,
+  "钠": 50332,
+  "钡": 52177,
+  "钢": 49415,
+  "钣": 52115,
+  "钦": 50889,
+  "钧": 51691,
+  "钨": 51763,
+  "钩": 50139,
+  "钯": 52473,
+  "钰": 50974,
+  "钳": 51282,
+  "钴": 51455,
+  "钵": 52110,
+  "钻": 49968,
+  "钼": 51717,
+  "钽": 53067,
+  "钾": 50678,
+  "铀": 51527,
+  "铁": 49265,
+  "铂": 51488,
+  "铃": 50098,
+  "铅": 50657,
+  "铆": 52551,
+  "铈": 52586,
+  "铋": 52828,
+  "铌": 52621,
+  "铎": 51945,
+  "铐": 51863,
+  "铖": 52741,
+  "铛": 51750,
+  "铜": 49956,
+  "铝": 49913,
+  "铟": 52849,
+  "铠": 51399,
+  "铢": 52486,
+  "铣": 51316,
+  "铬": 51429,
+  "铭": 50264,
+  "铮": 52117,
+  "铰": 51908,
+  "铱": 52659,
+  "铲": 50941,
+  "铵": 51410,
+  "铸": 50403,
+  "铺": 49633,
+  "铿": 52478,
+  "锂": 50276,
+  "锄": 52439,
+  "锅": 49688,
+  "锆": 51536,
+  "锈": 50312,
+  "锉": 53048,
+  "锋": 49845,
+  "锌": 50719,
+  "锐": 50019,
+  "锑": 53024,
+  "锗": 52686,
+  "锚": 50934,
+  "锟": 53070,
+  "锡": 50447,
+  "锢": 52252,
+  "锣": 51817,
+  "锤": 50469,
+  "锥": 50749,
+  "锦": 50197,
+  "锭": 52178,
+  "锯": 51042,
+  "锰": 51306,
+  "锲": 52524,
+  "锵": 52263,
+  "锻": 49494,
+  "镀": 50899,
+  "镁": 50916,
+  "镂": 52282,
+  "镉": 52034,
+  "镍": 51069,
+  "镐": 52707,
+  "镑": 51995,
+  "镓": 51959,
+  "镖": 51274,
+  "镣": 52751,
+  "镧": 53007,
+  "镭": 52003,
+  "镯": 51639,
+  "镰": 52188,
+  "镶": 51304,
+  "門": 51900,
+  "閉": 52937,
+  "閣": 53500,
+  "閲": 54121,
+  "闘": 52863,
+  "關": 51743,
+  "闪": 49598,
+  "闫": 51962,
+  "闯": 50755,
+  "闰": 50922,
+  "闲": 49651,
+  "闵": 51723,
+  "闷": 50790,
+  "闸": 50999,
+  "闹": 50271,
+  "闺": 51149,
+  "闽": 51272,
+  "阀": 50217,
+  "阁": 50542,
+  "阂": 51648,
+  "阆": 52813,
+  "阈": 49908,
+  "阉": 52471,
+  "阎": 51782,
+  "阐": 49766,
+  "阑": 51708,
+  "阔": 49665,
+  "阖": 52740,
+  "阙": 52070,
+  "阜": 51386,
+  "阪": 51860,
+  "阮": 51459,
+  "阱": 50540,
+  "阴": 49280,
+  "陀": 50631,
+  "陂": 52624,
+  "陇": 52135,
+  "陋": 51066,
+  "陌": 50049,
+  "陕": 50458,
+  "陛": 51515,
+  "陡": 51313,
+  "陣": 53969,
+  "陥": 54019,
+  "陨": 50946,
+  "陪": 49625,
+  "陰": 52460,
+  "陵": 50284,
+  "陶": 49893,
+  "陷": 49429,
+  "陸": 53258,
+  "険": 52619,
+  "陽": 52226,
+  "隅": 52335,
+  "隆": 49947,
+  "隊": 52677,
+  "隋": 51516,
+  "隍": 52160,
+  "階": 53450,
+  "隘": 51999,
+  "隙": 50215,
+  "際": 52020,
+  "隠": 52953,
+  "隣": 53755,
+  "隧": 50409,
+  "隨": 52423,
+  "險": 52891,
+  "隶": 50186,
+  "隷": 54075,
+  "隻": 54033,
+  "隼": 53057,
+  "隽": 53032,
+  "雀": 50633,
+  "雁": 51041,
+  "雄": 49390,
+  "雅": 49410,
+  "雇": 50349,
+  "雉": 52885,
+  "雌": 50704,
+  "雍": 51533,
+  "雎": 52358,
+  "雏": 51637,
+  "雑": 53574,
+  "雕": 50092,
+  "離": 52217,
+  "難": 52168,
+  "雨": 49359,
+  "雪": 49373,
+  "雯": 50873,
+  "雲": 52696,
+  "雳": 52445,
+  "雷": 49399,
+  "雹": 52267,
+  "雾": 49964,
+  "霁": 52785,
+  "霄": 50966,
+  "霆": 51328,
+  "震": 49517,
+  "霉": 50685,
+  "霊": 53718,
+  "霍": 50298,
+  "霏": 52480,
+  "霓": 51588,
+  "霖": 51311,
+  "霜": 50223,
+  "霞": 50667,
+  "霰": 52757,
+  "露": 49238,
+  "霸": 50128,
+  "霹": 52441,
+  "霾": 51526,
+  "靓": 51686,
+  "靖": 50740,
+  "靠": 49182,
+  "靡": 51216,
+  "靳": 52944,
+  "靴": 51029,
+  "靶": 50791,
+  "鞅": 52566,
+  "鞋": 49597,
+  "鞍": 51512,
+  "鞑": 51952,
+  "鞘": 51935,
+  "鞠": 51634,
+  "鞭": 50893,
+  "韓": 53462,
+  "韦": 50591,
+  "韧": 49949,
+  "韩": 49671,
+  "韬": 52314,
+  "韭": 51625,
+  "韵": 50073,
+  "韶": 51280,
+  "響": 52041,
+  "頂": 53010,
+  "頃": 53023,
+  "須": 52351,
+  "預": 52954,
+  "頑": 52840,
+  "領": 52509,
+  "頭": 51853,
+  "頻": 53959,
+  "頼": 52729,
+  "額": 52421,
+  "顔": 51913,
+  "顕": 53826,
+  "願": 52047,
+  "顧": 53848,
+  "顯": 52866,
+  "顷": 51578,
+  "顽": 50836,
+  "顾": 49279,
+  "顿": 49612,
+  "颁": 50515,
+  "颂": 50799,
+  "颅": 51197,
+  "颇": 50590,
+  "颈": 49888,
+  "颊": 50900,
+  "颌": 51586,
+  "颍": 52546,
+  "颐": 51320,
+  "颓": 51858,
+  "颖": 50144,
+  "颗": 49675,
+  "颚": 52233,
+  "颞": 52169,
+  "颠": 50772,
+  "颤": 49978,
+  "颧": 52764,
+  "風": 51530,
+  "飒": 52154,
+  "飓": 52079,
+  "飘": 50249,
+  "飙": 51074,
+  "飛": 52349,
+  "飯": 52949,
+  "飲": 52333,
+  "飼": 54082,
+  "飽": 54164,
+  "飾": 53815,
+  "養": 52805,
+  "餐": 49209,
+  "館": 52817,
+  "餮": 53013,
+  "饕": 52732,
+  "饥": 50507,
+  "饨": 52234,
+  "饪": 50279,
+  "饭": 49537,
+  "饮": 49202,
+  "饯": 52770,
+  "饰": 49396,
+  "饱": 49981,
+  "饲": 50257,
+  "饵": 51122,
+  "饶": 51142,
+  "饺": 51009,
+  "饼": 50050,
+  "饿": 50395,
+  "馁": 51757,
+  "馄": 52210,
+  "馅": 51076,
+  "馆": 49341,
+  "馈": 49304,
+  "馋": 52348,
+  "馍": 51528,
+  "馏": 51119,
+  "馒": 51126,
+  "馔": 52354,
+  "馗": 52833,
+  "馥": 52250,
+  "馨": 49919,
+  "馬": 51897,
+  "駄": 52909,
+  "駅": 53398,
+  "駆": 53693,
+  "駐": 54148,
+  "騎": 52939,
+  "験": 52292,
+  "騙": 52790,
+  "驗": 52522,
+  "驚": 52658,
+  "驭": 51382,
+  "驯": 51475,
+  "驰": 50564,
+  "驳": 50751,
+  "驴": 51394,
+  "驶": 49431,
+  "驹": 52141,
+  "驻": 50426,
+  "驼": 50861,
+  "驾": 49425,
+  "驿": 51168,
+  "骁": 50875,
+  "骂": 50196,
+  "骄": 50737,
+  "骆": 51253,
+  "骇": 52077,
+  "骊": 52862,
+  "骋": 52131,
+  "骏": 51222,
+  "骐": 52974,
+  "骑": 49741,
+  "骗": 49701,
+  "骚": 49983,
+  "骛": 52900,
+  "骞": 53000,
+  "骥": 52934,
+  "骨": 49464,
+  "骰": 50940,
+  "骷": 51769,
+  "骸": 51789,
+  "骼": 50621,
+  "髂": 53014,
+  "髄": 54112,
+  "髅": 51785,
+  "髋": 51968,
+  "髓": 50470,
+  "體": 51491,
+  "髦": 52337,
+  "髪": 54096,
+  "髻": 52629,
+  "鬃": 53051,
+  "鬓": 52083,
+  "鬟": 52600,
+  "鬼": 49724,
+  "魁": 51296,
+  "魂": 49672,
+  "魄": 50800,
+  "魅": 49357,
+  "魇": 52366,
+  "魈": 52413,
+  "魏": 50407,
+  "魔": 49210,
+  "魚": 53685,
+  "鮮": 53560,
+  "鱿": 52244,
+  "鲁": 49566,
+  "鲈": 51667,
+  "鲍": 51169,
+  "鲑": 52410,
+  "鲜": 49325,
+  "鲟": 52923,
+  "鲢": 52766,
+  "鲤": 51255,
+  "鲨": 51082,
+  "鲫": 51614,
+  "鲲": 52009,
+  "鲶": 52491,
+  "鲸": 50925,
+  "鳃": 52744,
+  "鳄": 51227,
+  "鳅": 52635,
+  "鳌": 51937,
+  "鳍": 51803,
+  "鳕": 52305,
+  "鳖": 52555,
+  "鳗": 52085,
+  "鳜": 52698,
+  "鳝": 52850,
+  "鳞": 51105,
+  "鳥": 52780,
+  "鳴": 53038,
+  "鶴": 54102,
+  "鸟": 49661,
+  "鸠": 52017,
+  "鸡": 49312,
+  "鸢": 51360,
+  "鸣": 49781,
+  "鸥": 51876,
+  "鸦": 50783,
+  "鸭": 50322,
+  "鸯": 52183,
+  "鸳": 52193,
+  "鸵": 52636,
+  "鸽": 50957,
+  "鸾": 52058,
+  "鸿": 50503,
+  "鹃": 51947,
+  "鹅": 50625,
+  "鹉": 51307,
+  "鹊": 51866,
+  "鹌": 53006,
+  "鹏": 50496,
+  "鹑": 52901,
+  "鹜": 52750,
+  "鹤": 50584,
+  "鹦": 51295,
+  "鹫": 52655,
+  "鹭": 51980,
+  "鹰": 50574,
+  "鹳": 51754,
+  "鹿": 50523,
+  "麒": 51031,
+  "麓": 51131,
+  "麗": 52223,
+  "麝": 52739,
+  "麟": 50886,
+  "麦": 49695,
+  "麸": 52452,
+  "麻": 49548,
+  "麼": 51657,
+  "麽": 52973,
+  "麾": 52644,
+  "黎": 50328,
+  "黏": 50289,
+  "黒": 52593,
+  "黔": 51603,
+  "黛": 50498,
+  "黜": 52714,
+  "黝": 52760,
+  "點": 51977,
+  "黠": 52731,
+  "黨": 54139,
+  "黯": 51715,
+  "鼎": 50835,
+  "鼓": 49276,
+  "鼠": 49454,
+  "鼬": 52477,
+  "鼻": 50000,
+  "鼾": 52298,
+  "齢": 53798,
+  "齿": 49768,
+  "龄": 49393,
+  "龈": 51413,
+  "龋": 51874,
+  "龍": 52940,
+  "龚": 51855,
+  "龛": 52768,
+  "龟": 50148,
+  "갈": 53223,
+  "감": 53139,
+  "갑": 53548,
+  "갔": 53571,
+  "강": 53107,
+  "갖": 53335,
+  "같": 53129,
+  "객": 53396,
+  "갤": 53823,
+  "갱": 53989,
+  "건": 53123,
+  "걸": 53311,
+  "검": 53350,
+  "겁": 54166,
+  "겉": 53844,
+  "겐": 53603,
+  "겔": 53810,
+  "겨": 53269,
+  "겪": 53752,
+  "견": 53229,
+  "겸": 53598,
+  "겹": 53983,
+  "겼": 53584,
+  "곡": 53188,
+  "곤": 53502,
+  "곧": 53720,
+  "골": 53226,
+  "곰": 53878,
+  "곱": 53562,
+  "곳": 53268,
+  "곽": 54040,
+  "괄": 53729,
+  "광": 53167,
+  "괴": 53369,
+  "교": 53073,
+  "군": 53089,
+  "굳": 54029,
+  "굴": 53512,
+  "굽": 54063,
+  "궁": 53439,
+  "권": 53105,
+  "궐": 54092,
+  "궤": 53591,
+  "귀": 53313,
+  "규": 53191,
+  "균": 53365,
+  "극": 53196,
+  "글": 53144,
+  "급": 53162,
+  "긍": 54032,
+  "긴": 53352,
+  "길": 53282,
+  "김": 53375,
+  "깃": 53866,
+  "깊": 53643,
+  "깔": 53853,
+  "깝": 53929,
+  "깥": 53926,
+  "깨": 53633,
+  "꺼": 53973,
+  "꺾": 54000,
+  "껍": 54024,
+  "께": 53198,
+  "꼬": 53714,
+  "꼭": 53855,
+  "꼴": 54001,
+  "꼽": 53623,
+  "꽃": 53616,
+  "꾸": 53526,
+  "꾼": 54021,
+  "꿀": 54050,
+  "꿈": 53869,
+  "뀌": 53668,
+  "뀐": 54060,
+  "끄": 53744,
+  "끈": 53907,
+  "끊": 53968,
+  "끌": 53482,
+  "끓": 54099,
+  "끔": 53912,
+  "끝": 53348,
+  "끼": 53463,
+  "낌": 54104,
+  "낙": 53691,
+  "난": 53164,
+  "날": 53197,
+  "남": 53090,
+  "납": 53741,
+  "났": 53371,
+  "낭": 53723,
+  "낮": 53505,
+  "낱": 53772,
+  "낳": 53778,
+  "낸": 53357,
+  "낼": 53785,
+  "냄": 54073,
+  "냈": 53457,
+  "냉": 53738,
+  "냐": 53513,
+  "냥": 53754,
+  "너": 53192,
+  "넌": 53967,
+  "널": 53213,
+  "넓": 53446,
+  "넘": 53372,
+  "넣": 53596,
+  "네": 53100,
+  "넥": 53874,
+  "넨": 53950,
+  "넬": 53780,
+  "넷": 53394,
+  "녀": 53337,
+  "념": 53278,
+  "녔": 54123,
+  "노": 53085,
+  "녹": 53442,
+  "논": 53288,
+  "놀": 53642,
+  "놈": 54048,
+  "농": 53359,
+  "높": 53243,
+  "놓": 53520,
+  "뇌": 53528,
+  "뇨": 53906,
+  "누": 53237,
+  "눅": 53689,
+  "눈": 53510,
+  "눌": 53843,
+  "뉘": 53615,
+  "뉜": 53725,
+  "뉴": 53225,
+  "늄": 53636,
+  "느": 53368,
+  "늑": 54051,
+  "늘": 53286,
+  "늦": 54105,
+  "늬": 53792,
+  "닉": 53489,
+  "닌": 53303,
+  "닐": 53724,
+  "님": 53630,
+  "닛": 53856,
+  "닝": 53628,
+  "닥": 53681,
+  "닫": 54085,
+  "달": 53125,
+  "닭": 53995,
+  "닮": 54097,
+  "담": 53267,
+  "답": 53827,
+  "닷": 53936,
+  "닿": 54003,
+  "댄": 53824,
+  "덕": 53451,
+  "던": 53112,
+  "덜": 53401,
+  "덟": 54107,
+  "덤": 53735,
+  "덧": 54071,
+  "덩": 53832,
+  "덮": 53839,
+  "덱": 53958,
+  "덴": 53304,
+  "독": 53083,
+  "돈": 53569,
+  "돌": 53244,
+  "돔": 53976,
+  "돕": 54150,
+  "돼": 53767,
+  "됐": 53435,
+  "될": 53336,
+  "됨": 53715,
+  "둑": 54004,
+  "둔": 53580,
+  "둘": 53402,
+  "둥": 53554,
+  "뒤": 53280,
+  "뒷": 53871,
+  "듀": 53507,
+  "듈": 54116,
+  "듐": 54115,
+  "득": 53381,
+  "듣": 53852,
+  "듬": 53674,
+  "듭": 54043,
+  "듯": 53789,
+  "등": 53074,
+  "딕": 53781,
+  "딘": 53653,
+  "딜": 53917,
+  "딩": 53529,
+  "따": 53117,
+  "딱": 54056,
+  "딴": 53924,
+  "딸": 53609,
+  "땅": 53631,
+  "때": 53093,
+  "떠": 53508,
+  "떤": 53484,
+  "떨": 53434,
+  "떻": 53889,
+  "또": 53082,
+  "똑": 54076,
+  "뚜": 53984,
+  "뛰": 53488,
+  "뜨": 53709,
+  "뜻": 53231,
+  "띄": 53985,
+  "띠": 53734,
+  "띤": 54038,
+  "락": 53334,
+  "란": 53101,
+  "랄": 53656,
+  "람": 53145,
+  "랍": 53445,
+  "랐": 53493,
+  "랑": 53111,
+  "랙": 53487,
+  "랜": 53146,
+  "랩": 53897,
+  "랫": 53527,
+  "랭": 53556,
+  "랴": 53915,
+  "략": 53470,
+  "량": 53174,
+  "럭": 53634,
+  "런": 53236,
+  "럴": 53654,
+  "럼": 53284,
+  "럽": 53147,
+  "럿": 54018,
+  "렀": 53552,
+  "렇": 53635,
+  "렉": 53393,
+  "렌": 53326,
+  "렐": 53850,
+  "렘": 53811,
+  "렛": 53911,
+  "렬": 53576,
+  "렴": 53905,
+  "렵": 53680,
+  "렷": 54114,
+  "렸": 53307,
+  "령": 53152,
+  "례": 53312,
+  "론": 53142,
+  "롤": 53414,
+  "롬": 53599,
+  "롭": 53582,
+  "롯": 53377,
+  "롱": 53666,
+  "뢰": 53639,
+  "룡": 53784,
+  "루": 53087,
+  "룩": 53655,
+  "룬": 53506,
+  "룰": 53875,
+  "룸": 53797,
+  "룹": 53341,
+  "룽": 54042,
+  "뤄": 53884,
+  "뤼": 53758,
+  "륙": 53374,
+  "륜": 53935,
+  "률": 53386,
+  "륨": 53648,
+  "륭": 54132,
+  "릉": 53804,
+  "릭": 53305,
+  "린": 53127,
+  "릴": 53407,
+  "림": 53182,
+  "릿": 53625,
+  "막": 53207,
+  "많": 53116,
+  "말": 53104,
+  "맘": 54081,
+  "맛": 53746,
+  "망": 53200,
+  "맞": 53370,
+  "맡": 53329,
+  "맥": 53298,
+  "맨": 53364,
+  "맵": 54159,
+  "맷": 53730,
+  "맹": 53321,
+  "맺": 53670,
+  "머": 53203,
+  "먹": 53465,
+  "먼": 53272,
+  "멀": 53581,
+  "멍": 54028,
+  "메": 53092,
+  "멕": 53573,
+  "멘": 53517,
+  "멜": 53638,
+  "멤": 53544,
+  "멸": 53409,
+  "몇": 53392,
+  "몬": 53362,
+  "몰": 53461,
+  "몸": 53452,
+  "못": 53324,
+  "몽": 53420,
+  "묘": 53485,
+  "묵": 53980,
+  "묶": 53849,
+  "묻": 54113,
+  "물": 53078,
+  "뮌": 53761,
+  "뮤": 53448,
+  "뮬": 53954,
+  "므": 53378,
+  "믹": 53662,
+  "민": 53079,
+  "믿": 53676,
+  "밀": 53210,
+  "밍": 53490,
+  "및": 53153,
+  "밑": 53807,
+  "박": 53233,
+  "밖": 53534,
+  "받": 53120,
+  "밝": 53455,
+  "밤": 53712,
+  "밥": 53888,
+  "방": 53077,
+  "배": 53110,
+  "백": 53190,
+  "밴": 53412,
+  "밸": 54061,
+  "뱀": 53914,
+  "뱅": 53740,
+  "벌": 53293,
+  "범": 53189,
+  "벗": 53865,
+  "베": 53096,
+  "벡": 53769,
+  "벤": 53433,
+  "벨": 53259,
+  "벳": 53992,
+  "벵": 54025,
+  "벼": 53903,
+  "벽": 53553,
+  "병": 53169,
+  "볼": 53240,
+  "봄": 53885,
+  "봇": 53937,
+  "봉": 53290,
+  "북": 53126,
+  "불": 53097,
+  "붉": 53770,
+  "붓": 53944,
+  "붕": 53530,
+  "붙": 53391,
+  "뷔": 53356,
+  "뷰": 53760,
+  "븐": 53750,
+  "빅": 53608,
+  "빈": 53366,
+  "빌": 53292,
+  "빗": 53913,
+  "빙": 53593,
+  "빛": 53511,
+  "빠": 53458,
+  "빨": 53592,
+  "빵": 53978,
+  "빼": 53893,
+  "뻗": 53997,
+  "뼈": 53669,
+  "뽑": 53919,
+  "뿌": 53808,
+  "뿐": 53417,
+  "뿔": 53862,
+  "삭": 53719,
+  "살": 53183,
+  "삶": 53732,
+  "삼": 53234,
+  "삽": 53946,
+  "새": 53218,
+  "샌": 53692,
+  "샘": 53763,
+  "샤": 53351,
+  "샬": 54120,
+  "샹": 54068,
+  "섞": 53883,
+  "설": 53095,
+  "섬": 53239,
+  "섭": 53600,
+  "섯": 53549,
+  "섰": 53979,
+  "섹": 53932,
+  "센": 53264,
+  "셀": 53416,
+  "셈": 53644,
+  "셉": 53964,
+  "셋": 53836,
+  "셔": 53479,
+  "셜": 53673,
+  "셰": 53597,
+  "셸": 53842,
+  "손": 53270,
+  "솔": 53503,
+  "솜": 54144,
+  "송": 53177,
+  "쇄": 53577,
+  "쇠": 53704,
+  "쇼": 53467,
+  "숙": 53537,
+  "순": 53195,
+  "술": 53154,
+  "숨": 53809,
+  "숫": 53690,
+  "숭": 53651,
+  "숲": 53943,
+  "쉐": 54153,
+  "쉬": 53564,
+  "쉽": 53583,
+  "슈": 53215,
+  "슐": 53863,
+  "슘": 53947,
+  "슨": 53317,
+  "슬": 53181,
+  "슴": 53861,
+  "슷": 53469,
+  "승": 53103,
+  "십": 53388,
+  "싱": 53253,
+  "싶": 54047,
+  "싸": 53471,
+  "싼": 53925,
+  "쌀": 54077,
+  "쌍": 53585,
+  "쌓": 53846,
+  "써": 53346,
+  "썬": 54089,
+  "썼": 53743,
+  "쏘": 54147,
+  "쓰": 53172,
+  "쓴": 53595,
+  "쓸": 53872,
+  "씨": 53405,
+  "씩": 53622,
+  "씬": 53817,
+  "악": 53161,
+  "앉": 54046,
+  "않": 53124,
+  "알": 53094,
+  "암": 53251,
+  "압": 53300,
+  "앗": 53909,
+  "았": 53143,
+  "앙": 53242,
+  "앞": 53472,
+  "애": 53156,
+  "액": 53344,
+  "앤": 53432,
+  "앨": 53325,
+  "앱": 53930,
+  "앵": 53762,
+  "얀": 53602,
+  "얄": 54108,
+  "얇": 54129,
+  "양": 53088,
+  "억": 53343,
+  "얻": 53361,
+  "얼": 53363,
+  "엄": 53347,
+  "없": 53168,
+  "엇": 53834,
+  "엉": 54101,
+  "엑": 53660,
+  "엔": 53216,
+  "엘": 53276,
+  "엠": 53774,
+  "엣": 54022,
+  "염": 53283,
+  "엽": 53742,
+  "였": 53072,
+  "옆": 54094,
+  "예": 53106,
+  "옌": 54057,
+  "옛": 53613,
+  "옥": 53475,
+  "온": 53160,
+  "올": 53150,
+  "옮": 53659,
+  "옴": 54106,
+  "옵": 54044,
+  "옷": 53858,
+  "옹": 53546,
+  "완": 53260,
+  "왈": 54140,
+  "왓": 54141,
+  "왔": 53345,
+  "왕": 53102,
+  "왜": 53658,
+  "왼": 53851,
+  "욕": 53383,
+  "욱": 53675,
+  "울": 53211,
+  "움": 53281,
+  "웃": 53683,
+  "웅": 53701,
+  "웠": 53606,
+  "웨": 53157,
+  "웰": 53745,
+  "웹": 53422,
+  "윈": 53295,
+  "윌": 53539,
+  "윗": 54131,
+  "윙": 53923,
+  "육": 53204,
+  "윤": 53532,
+  "율": 53323,
+  "융": 53543,
+  "읍": 53716,
+  "응": 53263,
+  "익": 53376,
+  "읽": 53722,
+  "잃": 53764,
+  "잇": 53687,
+  "있": 53071,
+  "잉": 53322,
+  "잎": 53694,
+  "잔": 53477,
+  "잘": 53340,
+  "잠": 53492,
+  "잡": 53297,
+  "잭": 53649,
+  "쟁": 53171,
+  "절": 53179,
+  "젊": 53880,
+  "젖": 54041,
+  "젠": 53557,
+  "젤": 53516,
+  "졌": 53208,
+  "족": 53140,
+  "존": 53132,
+  "졸": 53612,
+  "좀": 53882,
+  "좁": 53794,
+  "종": 53084,
+  "좋": 53515,
+  "좌": 53421,
+  "죄": 53518,
+  "죽": 53387,
+  "줄": 53266,
+  "줌": 54152,
+  "쥐": 53626,
+  "즈": 53119,
+  "즉": 53310,
+  "즌": 53261,
+  "즐": 53663,
+  "즘": 53415,
+  "증": 53175,
+  "질": 53108,
+  "짐": 53713,
+  "짓": 53684,
+  "징": 53257,
+  "짜": 53664,
+  "짝": 54009,
+  "짧": 53601,
+  "짱": 54170,
+  "쪽": 53131,
+  "쫓": 54149,
+  "찌": 53957,
+  "찍": 53782,
+  "착": 53330,
+  "찬": 53397,
+  "찰": 53367,
+  "참": 53193,
+  "창": 53186,
+  "찾": 53538,
+  "채": 53255,
+  "책": 53274,
+  "챔": 53429,
+  "척": 53474,
+  "천": 53130,
+  "철": 53173,
+  "첨": 53776,
+  "첩": 53840,
+  "첫": 53249,
+  "첸": 53900,
+  "첼": 53768,
+  "쳐": 53277,
+  "쳤": 53575,
+  "초": 53099,
+  "촉": 53586,
+  "촌": 53671,
+  "총": 53155,
+  "촬": 53661,
+  "최": 53091,
+  "추": 53141,
+  "축": 53115,
+  "춘": 53568,
+  "춤": 53895,
+  "충": 53273,
+  "춰": 54062,
+  "취": 53287,
+  "츠": 53205,
+  "측": 53252,
+  "층": 53385,
+  "칙": 53408,
+  "친": 53271,
+  "칠": 53486,
+  "침": 53319,
+  "칩": 53887,
+  "칭": 53158,
+  "칸": 53320,
+  "칼": 53315,
+  "캄": 53705,
+  "캅": 53977,
+  "캐": 53248,
+  "캔": 53854,
+  "캘": 53588,
+  "캠": 53667,
+  "캡": 54074,
+  "커": 53232,
+  "컨": 53480,
+  "컫": 53617,
+  "컬": 53390,
+  "컴": 53221,
+  "컵": 53224,
+  "컷": 53688,
+  "케": 53178,
+  "켄": 53727,
+  "켈": 53645,
+  "켓": 53525,
+  "켜": 53524,
+  "켰": 53521,
+  "코": 53086,
+  "콕": 54035,
+  "콘": 53285,
+  "콜": 53302,
+  "콤": 53702,
+  "콥": 53910,
+  "콧": 54027,
+  "콩": 53545,
+  "콰": 54052,
+  "쾌": 53974,
+  "쿄": 53551,
+  "쿠": 53199,
+  "쿤": 54145,
+  "쿨": 53759,
+  "쿼": 53757,
+  "퀘": 53831,
+  "퀴": 53697,
+  "퀸": 53756,
+  "큐": 53621,
+  "큰": 53220,
+  "클": 53149,
+  "큼": 53765,
+  "킥": 54036,
+  "킨": 53306,
+  "킬": 53535,
+  "킴": 54080,
+  "킷": 53886,
+  "킹": 53478,
+  "탁": 53650,
+  "탄": 53166,
+  "탈": 53148,
+  "탐": 53466,
+  "탑": 53550,
+  "탕": 53440,
+  "탠": 53828,
+  "탱": 54013,
+  "턱": 54136,
+  "털": 53379,
+  "테": 53113,
+  "텍": 53533,
+  "텐": 53413,
+  "텔": 53327,
+  "톡": 53982,
+  "톤": 53427,
+  "톨": 53437,
+  "톰": 53822,
+  "톱": 53698,
+  "통": 53076,
+  "퇴": 53355,
+  "투": 53121,
+  "툰": 53904,
+  "툴": 53892,
+  "툼": 54134,
+  "튀": 53495,
+  "튜": 53453,
+  "튬": 54128,
+  "특": 53122,
+  "튼": 53519,
+  "틀": 53246,
+  "틈": 54174,
+  "틱": 53547,
+  "틴": 53256,
+  "틸": 53657,
+  "팀": 53163,
+  "팅": 53444,
+  "판": 53137,
+  "팔": 53314,
+  "팜": 54158,
+  "팝": 53699,
+  "팟": 54088,
+  "팡": 54127,
+  "패": 53217,
+  "팩": 53795,
+  "팬": 53620,
+  "팽": 53791,
+  "퍼": 53180,
+  "펀": 53838,
+  "펄": 53879,
+  "펑": 53868,
+  "페": 53109,
+  "펙": 53803,
+  "펜": 53509,
+  "펠": 53589,
+  "편": 53138,
+  "펼": 53717,
+  "평": 53136,
+  "폐": 53332,
+  "폭": 53291,
+  "폰": 53353,
+  "폴": 53227,
+  "폼": 53579,
+  "퐁": 54130,
+  "푸": 53331,
+  "풀": 53460,
+  "품": 53151,
+  "풋": 53773,
+  "풍": 53395,
+  "퓌": 54146,
+  "퓨": 53245,
+  "픈": 53624,
+  "피": 53098,
+  "픽": 53247,
+  "핀": 53404,
+  "필": 53185,
+  "핍": 54169,
+  "핑": 53682,
+  "핫": 53821,
+  "항": 53114,
+  "핵": 53309,
+  "핸": 54020,
+  "햄": 53845,
+  "햇": 54014,
+  "허": 53294,
+  "헌": 53342,
+  "헐": 54037,
+  "험": 53265,
+  "헝": 53540,
+  "헤": 53250,
+  "헨": 53430,
+  "헬": 53494,
+  "혀": 53499,
+  "혁": 53299,
+  "혈": 53431,
+  "혐": 53956,
+  "협": 53238,
+  "혔": 53710,
+  "혜": 53619,
+  "혹": 53308,
+  "혼": 53279,
+  "홀": 53476,
+  "홈": 53468,
+  "홉": 54093,
+  "홋": 53981,
+  "홍": 53459,
+  "확": 53184,
+  "활": 53133,
+  "황": 53135,
+  "획": 53338,
+  "횡": 54026,
+  "효": 53275,
+  "후": 53075,
+  "훈": 53522,
+  "훌": 53994,
+  "훗": 54072,
+  "훨": 53860,
+  "휘": 53419,
+  "휴": 53436,
+  "흉": 53993,
+  "흐": 53328,
+  "흑": 53555,
+  "흔": 53424,
+  "흘": 53783,
+  "흙": 54098,
+  "흡": 53558,
+  "흥": 53483,
+  "희": 53426,
+  "흰": 53749,
+  "힌": 53464,
+  "힐": 53766,
+  "힘": 53443,
+  "힙": 53899,
+  "％": 53965,
+  "／": 53859,
+  "＝": 53400
+}

config.json

@@ -0,0 +1,39 @@
+{
+  "_name_or_path": "openbuddy-coder-v10",
+  "activation_function": "gelu",
+  "architectures": [
+    "GPTBigCodeForCausalLM"
+  ],
+  "attention_softmax_in_fp32": true,
+  "attn_pdrop": 0.1,
+  "bos_token_id": 0,
+  "embd_pdrop": 0.1,
+  "eos_token_id": 0,
+  "inference_runner": 0,
+  "initializer_range": 0.02,
+  "layer_norm_epsilon": 1e-05,
+  "max_batch_size": null,
+  "max_sequence_length": null,
+  "model_type": "gpt_bigcode",
+  "multi_query": true,
+  "n_embd": 6144,
+  "n_head": 48,
+  "n_inner": 24576,
+  "n_layer": 40,
+  "n_positions": 8192,
+  "pad_key_length": true,
+  "pre_allocate_kv_cache": false,
+  "resid_pdrop": 0.1,
+  "scale_attention_softmax_in_fp32": true,
+  "scale_attn_weights": true,
+  "summary_activation": null,
+  "summary_first_dropout": 0.1,
+  "summary_proj_to_labels": true,
+  "summary_type": "cls_index",
+  "summary_use_proj": true,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.31.0",
+  "use_cache": true,
+  "validate_runner_input": true,
+  "vocab_size": 54272
+}

generation_config.json

@@ -0,0 +1,6 @@
+{
+  "_from_model_config": true,
+  "bos_token_id": 0,
+  "eos_token_id": 0,
+  "transformers_version": "4.31.0"
+}

pytorch_model-00001-of-00004.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:557222f34a458ed7bd6db0a9e6d7f8f2c3dfe71b0e6163a8c5d431b88fa5f505
+size 9945361785

pytorch_model-00002-of-00004.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e8ec7ae0d875c70cf960a6b2cb56098c2f9410135e96344c43825175401d4521
+size 9932917347

pytorch_model-00003-of-00004.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e17d822948f262eb31366e363b2081b5c7b435572f2fc2c998ae4f5c02147d93
+size 9857381671

pytorch_model-00004-of-00004.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:9c3857c4f4c77bae01ea92448d0ad115164c1d01655ccb0d34f089440798a358
+size 1362327955

pytorch_model.bin.index.json

@@ -0,0 +1,492 @@
+{
+  "metadata": {
+    "total_size": 31097827328
+  },
+  "weight_map": {
+    "lm_head.weight": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.0.attn.c_attn.bias": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.0.attn.c_attn.weight": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.0.attn.c_proj.bias": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.0.attn.c_proj.weight": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.0.ln_1.bias": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.0.ln_1.weight": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.0.ln_2.bias": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.0.ln_2.weight": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.0.mlp.c_fc.bias": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.0.mlp.c_fc.weight": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.0.mlp.c_proj.bias": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.0.mlp.c_proj.weight": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.1.attn.c_attn.bias": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.1.attn.c_attn.weight": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.1.attn.c_proj.bias": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.1.attn.c_proj.weight": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.1.ln_1.bias": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.1.ln_1.weight": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.1.ln_2.bias": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.1.ln_2.weight": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.1.mlp.c_fc.bias": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.1.mlp.c_fc.weight": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.1.mlp.c_proj.bias": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.1.mlp.c_proj.weight": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.10.attn.c_attn.bias": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.10.attn.c_attn.weight": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.10.attn.c_proj.bias": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.10.attn.c_proj.weight": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.10.ln_1.bias": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.10.ln_1.weight": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.10.ln_2.bias": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.10.ln_2.weight": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.10.mlp.c_fc.bias": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.10.mlp.c_fc.weight": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.10.mlp.c_proj.bias": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.10.mlp.c_proj.weight": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.11.attn.c_attn.bias": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.11.attn.c_attn.weight": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.11.attn.c_proj.bias": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.11.attn.c_proj.weight": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.11.ln_1.bias": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.11.ln_1.weight": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.11.ln_2.bias": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.11.ln_2.weight": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.11.mlp.c_fc.bias": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.11.mlp.c_fc.weight": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.11.mlp.c_proj.bias": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.11.mlp.c_proj.weight": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.12.attn.c_attn.bias": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.12.attn.c_attn.weight": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.12.attn.c_proj.bias": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.12.attn.c_proj.weight": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.12.ln_1.bias": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.12.ln_1.weight": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.12.ln_2.bias": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.12.ln_2.weight": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.12.mlp.c_fc.bias": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.12.mlp.c_fc.weight": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.12.mlp.c_proj.bias": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.12.mlp.c_proj.weight": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.13.attn.c_attn.bias": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.13.attn.c_attn.weight": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.13.attn.c_proj.bias": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.13.attn.c_proj.weight": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.13.ln_1.bias": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.13.ln_1.weight": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.13.ln_2.bias": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.13.ln_2.weight": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.13.mlp.c_fc.bias": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.13.mlp.c_fc.weight": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.13.mlp.c_proj.bias": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.13.mlp.c_proj.weight": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.14.attn.c_attn.bias": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.14.attn.c_attn.weight": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.14.attn.c_proj.bias": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.14.attn.c_proj.weight": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.14.ln_1.bias": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.14.ln_1.weight": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.14.ln_2.bias": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.14.ln_2.weight": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.14.mlp.c_fc.bias": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.14.mlp.c_fc.weight": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.14.mlp.c_proj.bias": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.14.mlp.c_proj.weight": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.15.attn.c_attn.bias": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.15.attn.c_attn.weight": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.15.attn.c_proj.bias": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.15.attn.c_proj.weight": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.15.ln_1.bias": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.15.ln_1.weight": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.15.ln_2.bias": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.15.ln_2.weight": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.15.mlp.c_fc.bias": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.15.mlp.c_fc.weight": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.15.mlp.c_proj.bias": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.15.mlp.c_proj.weight": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.16.attn.c_attn.bias": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.16.attn.c_attn.weight": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.16.attn.c_proj.bias": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.16.attn.c_proj.weight": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.16.ln_1.bias": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.16.ln_1.weight": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.16.ln_2.bias": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.16.ln_2.weight": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.16.mlp.c_fc.bias": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.16.mlp.c_fc.weight": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.16.mlp.c_proj.bias": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.16.mlp.c_proj.weight": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.17.attn.c_attn.bias": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.17.attn.c_attn.weight": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.17.attn.c_proj.bias": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.17.attn.c_proj.weight": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.17.ln_1.bias": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.17.ln_1.weight": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.17.ln_2.bias": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.17.ln_2.weight": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.17.mlp.c_fc.bias": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.17.mlp.c_fc.weight": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.17.mlp.c_proj.bias": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.17.mlp.c_proj.weight": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.18.attn.c_attn.bias": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.18.attn.c_attn.weight": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.18.attn.c_proj.bias": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.18.attn.c_proj.weight": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.18.ln_1.bias": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.18.ln_1.weight": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.18.ln_2.bias": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.18.ln_2.weight": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.18.mlp.c_fc.bias": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.18.mlp.c_fc.weight": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.18.mlp.c_proj.bias": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.18.mlp.c_proj.weight": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.19.attn.c_attn.bias": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.19.attn.c_attn.weight": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.19.attn.c_proj.bias": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.19.attn.c_proj.weight": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.19.ln_1.bias": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.19.ln_1.weight": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.19.ln_2.bias": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.19.ln_2.weight": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.19.mlp.c_fc.bias": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.19.mlp.c_fc.weight": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.19.mlp.c_proj.bias": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.19.mlp.c_proj.weight": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.2.attn.c_attn.bias": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.2.attn.c_attn.weight": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.2.attn.c_proj.bias": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.2.attn.c_proj.weight": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.2.ln_1.bias": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.2.ln_1.weight": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.2.ln_2.bias": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.2.ln_2.weight": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.2.mlp.c_fc.bias": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.2.mlp.c_fc.weight": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.2.mlp.c_proj.bias": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.2.mlp.c_proj.weight": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.20.attn.c_attn.bias": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.20.attn.c_attn.weight": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.20.attn.c_proj.bias": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.20.attn.c_proj.weight": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.20.ln_1.bias": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.20.ln_1.weight": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.20.ln_2.bias": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.20.ln_2.weight": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.20.mlp.c_fc.bias": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.20.mlp.c_fc.weight": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.20.mlp.c_proj.bias": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.20.mlp.c_proj.weight": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.21.attn.c_attn.bias": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.21.attn.c_attn.weight": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.21.attn.c_proj.bias": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.21.attn.c_proj.weight": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.21.ln_1.bias": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.21.ln_1.weight": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.21.ln_2.bias": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.21.ln_2.weight": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.21.mlp.c_fc.bias": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.21.mlp.c_fc.weight": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.21.mlp.c_proj.bias": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.21.mlp.c_proj.weight": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.22.attn.c_attn.bias": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.22.attn.c_attn.weight": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.22.attn.c_proj.bias": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.22.attn.c_proj.weight": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.22.ln_1.bias": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.22.ln_1.weight": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.22.ln_2.bias": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.22.ln_2.weight": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.22.mlp.c_fc.bias": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.22.mlp.c_fc.weight": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.22.mlp.c_proj.bias": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.22.mlp.c_proj.weight": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.23.attn.c_attn.bias": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.23.attn.c_attn.weight": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.23.attn.c_proj.bias": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.23.attn.c_proj.weight": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.23.ln_1.bias": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.23.ln_1.weight": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.23.ln_2.bias": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.23.ln_2.weight": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.23.mlp.c_fc.bias": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.23.mlp.c_fc.weight": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.23.mlp.c_proj.bias": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.23.mlp.c_proj.weight": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.24.attn.c_attn.bias": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.24.attn.c_attn.weight": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.24.attn.c_proj.bias": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.24.attn.c_proj.weight": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.24.ln_1.bias": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.24.ln_1.weight": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.24.ln_2.bias": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.24.ln_2.weight": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.24.mlp.c_fc.bias": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.24.mlp.c_fc.weight": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.24.mlp.c_proj.bias": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.24.mlp.c_proj.weight": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.25.attn.c_attn.bias": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.25.attn.c_attn.weight": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.25.attn.c_proj.bias": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.25.attn.c_proj.weight": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.25.ln_1.bias": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.25.ln_1.weight": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.25.ln_2.bias": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.25.ln_2.weight": "pytorch_model-00002-of-00004.bin",
+    "transformer.h.25.mlp.c_fc.bias": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.25.mlp.c_fc.weight": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.25.mlp.c_proj.bias": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.25.mlp.c_proj.weight": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.26.attn.c_attn.bias": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.26.attn.c_attn.weight": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.26.attn.c_proj.bias": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.26.attn.c_proj.weight": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.26.ln_1.bias": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.26.ln_1.weight": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.26.ln_2.bias": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.26.ln_2.weight": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.26.mlp.c_fc.bias": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.26.mlp.c_fc.weight": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.26.mlp.c_proj.bias": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.26.mlp.c_proj.weight": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.27.attn.c_attn.bias": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.27.attn.c_attn.weight": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.27.attn.c_proj.bias": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.27.attn.c_proj.weight": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.27.ln_1.bias": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.27.ln_1.weight": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.27.ln_2.bias": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.27.ln_2.weight": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.27.mlp.c_fc.bias": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.27.mlp.c_fc.weight": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.27.mlp.c_proj.bias": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.27.mlp.c_proj.weight": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.28.attn.c_attn.bias": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.28.attn.c_attn.weight": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.28.attn.c_proj.bias": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.28.attn.c_proj.weight": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.28.ln_1.bias": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.28.ln_1.weight": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.28.ln_2.bias": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.28.ln_2.weight": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.28.mlp.c_fc.bias": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.28.mlp.c_fc.weight": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.28.mlp.c_proj.bias": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.28.mlp.c_proj.weight": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.29.attn.c_attn.bias": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.29.attn.c_attn.weight": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.29.attn.c_proj.bias": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.29.attn.c_proj.weight": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.29.ln_1.bias": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.29.ln_1.weight": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.29.ln_2.bias": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.29.ln_2.weight": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.29.mlp.c_fc.bias": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.29.mlp.c_fc.weight": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.29.mlp.c_proj.bias": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.29.mlp.c_proj.weight": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.3.attn.c_attn.bias": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.3.attn.c_attn.weight": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.3.attn.c_proj.bias": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.3.attn.c_proj.weight": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.3.ln_1.bias": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.3.ln_1.weight": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.3.ln_2.bias": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.3.ln_2.weight": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.3.mlp.c_fc.bias": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.3.mlp.c_fc.weight": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.3.mlp.c_proj.bias": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.3.mlp.c_proj.weight": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.30.attn.c_attn.bias": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.30.attn.c_attn.weight": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.30.attn.c_proj.bias": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.30.attn.c_proj.weight": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.30.ln_1.bias": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.30.ln_1.weight": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.30.ln_2.bias": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.30.ln_2.weight": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.30.mlp.c_fc.bias": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.30.mlp.c_fc.weight": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.30.mlp.c_proj.bias": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.30.mlp.c_proj.weight": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.31.attn.c_attn.bias": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.31.attn.c_attn.weight": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.31.attn.c_proj.bias": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.31.attn.c_proj.weight": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.31.ln_1.bias": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.31.ln_1.weight": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.31.ln_2.bias": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.31.ln_2.weight": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.31.mlp.c_fc.bias": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.31.mlp.c_fc.weight": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.31.mlp.c_proj.bias": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.31.mlp.c_proj.weight": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.32.attn.c_attn.bias": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.32.attn.c_attn.weight": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.32.attn.c_proj.bias": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.32.attn.c_proj.weight": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.32.ln_1.bias": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.32.ln_1.weight": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.32.ln_2.bias": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.32.ln_2.weight": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.32.mlp.c_fc.bias": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.32.mlp.c_fc.weight": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.32.mlp.c_proj.bias": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.32.mlp.c_proj.weight": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.33.attn.c_attn.bias": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.33.attn.c_attn.weight": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.33.attn.c_proj.bias": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.33.attn.c_proj.weight": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.33.ln_1.bias": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.33.ln_1.weight": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.33.ln_2.bias": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.33.ln_2.weight": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.33.mlp.c_fc.bias": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.33.mlp.c_fc.weight": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.33.mlp.c_proj.bias": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.33.mlp.c_proj.weight": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.34.attn.c_attn.bias": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.34.attn.c_attn.weight": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.34.attn.c_proj.bias": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.34.attn.c_proj.weight": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.34.ln_1.bias": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.34.ln_1.weight": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.34.ln_2.bias": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.34.ln_2.weight": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.34.mlp.c_fc.bias": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.34.mlp.c_fc.weight": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.34.mlp.c_proj.bias": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.34.mlp.c_proj.weight": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.35.attn.c_attn.bias": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.35.attn.c_attn.weight": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.35.attn.c_proj.bias": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.35.attn.c_proj.weight": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.35.ln_1.bias": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.35.ln_1.weight": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.35.ln_2.bias": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.35.ln_2.weight": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.35.mlp.c_fc.bias": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.35.mlp.c_fc.weight": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.35.mlp.c_proj.bias": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.35.mlp.c_proj.weight": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.36.attn.c_attn.bias": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.36.attn.c_attn.weight": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.36.attn.c_proj.bias": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.36.attn.c_proj.weight": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.36.ln_1.bias": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.36.ln_1.weight": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.36.ln_2.bias": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.36.ln_2.weight": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.36.mlp.c_fc.bias": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.36.mlp.c_fc.weight": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.36.mlp.c_proj.bias": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.36.mlp.c_proj.weight": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.37.attn.c_attn.bias": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.37.attn.c_attn.weight": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.37.attn.c_proj.bias": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.37.attn.c_proj.weight": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.37.ln_1.bias": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.37.ln_1.weight": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.37.ln_2.bias": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.37.ln_2.weight": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.37.mlp.c_fc.bias": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.37.mlp.c_fc.weight": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.37.mlp.c_proj.bias": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.37.mlp.c_proj.weight": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.38.attn.c_attn.bias": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.38.attn.c_attn.weight": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.38.attn.c_proj.bias": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.38.attn.c_proj.weight": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.38.ln_1.bias": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.38.ln_1.weight": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.38.ln_2.bias": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.38.ln_2.weight": "pytorch_model-00003-of-00004.bin",
+    "transformer.h.38.mlp.c_fc.bias": "pytorch_model-00004-of-00004.bin",
+    "transformer.h.38.mlp.c_fc.weight": "pytorch_model-00004-of-00004.bin",
+    "transformer.h.38.mlp.c_proj.bias": "pytorch_model-00004-of-00004.bin",
+    "transformer.h.38.mlp.c_proj.weight": "pytorch_model-00004-of-00004.bin",
+    "transformer.h.39.attn.c_attn.bias": "pytorch_model-00004-of-00004.bin",
+    "transformer.h.39.attn.c_attn.weight": "pytorch_model-00004-of-00004.bin",
+    "transformer.h.39.attn.c_proj.bias": "pytorch_model-00004-of-00004.bin",
+    "transformer.h.39.attn.c_proj.weight": "pytorch_model-00004-of-00004.bin",
+    "transformer.h.39.ln_1.bias": "pytorch_model-00004-of-00004.bin",
+    "transformer.h.39.ln_1.weight": "pytorch_model-00004-of-00004.bin",
+    "transformer.h.39.ln_2.bias": "pytorch_model-00004-of-00004.bin",
+    "transformer.h.39.ln_2.weight": "pytorch_model-00004-of-00004.bin",
+    "transformer.h.39.mlp.c_fc.bias": "pytorch_model-00004-of-00004.bin",
+    "transformer.h.39.mlp.c_fc.weight": "pytorch_model-00004-of-00004.bin",
+    "transformer.h.39.mlp.c_proj.bias": "pytorch_model-00004-of-00004.bin",
+    "transformer.h.39.mlp.c_proj.weight": "pytorch_model-00004-of-00004.bin",
+    "transformer.h.4.attn.c_attn.bias": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.4.attn.c_attn.weight": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.4.attn.c_proj.bias": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.4.attn.c_proj.weight": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.4.ln_1.bias": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.4.ln_1.weight": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.4.ln_2.bias": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.4.ln_2.weight": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.4.mlp.c_fc.bias": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.4.mlp.c_fc.weight": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.4.mlp.c_proj.bias": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.4.mlp.c_proj.weight": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.5.attn.c_attn.bias": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.5.attn.c_attn.weight": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.5.attn.c_proj.bias": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.5.attn.c_proj.weight": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.5.ln_1.bias": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.5.ln_1.weight": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.5.ln_2.bias": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.5.ln_2.weight": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.5.mlp.c_fc.bias": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.5.mlp.c_fc.weight": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.5.mlp.c_proj.bias": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.5.mlp.c_proj.weight": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.6.attn.c_attn.bias": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.6.attn.c_attn.weight": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.6.attn.c_proj.bias": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.6.attn.c_proj.weight": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.6.ln_1.bias": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.6.ln_1.weight": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.6.ln_2.bias": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.6.ln_2.weight": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.6.mlp.c_fc.bias": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.6.mlp.c_fc.weight": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.6.mlp.c_proj.bias": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.6.mlp.c_proj.weight": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.7.attn.c_attn.bias": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.7.attn.c_attn.weight": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.7.attn.c_proj.bias": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.7.attn.c_proj.weight": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.7.ln_1.bias": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.7.ln_1.weight": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.7.ln_2.bias": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.7.ln_2.weight": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.7.mlp.c_fc.bias": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.7.mlp.c_fc.weight": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.7.mlp.c_proj.bias": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.7.mlp.c_proj.weight": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.8.attn.c_attn.bias": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.8.attn.c_attn.weight": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.8.attn.c_proj.bias": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.8.attn.c_proj.weight": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.8.ln_1.bias": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.8.ln_1.weight": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.8.ln_2.bias": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.8.ln_2.weight": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.8.mlp.c_fc.bias": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.8.mlp.c_fc.weight": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.8.mlp.c_proj.bias": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.8.mlp.c_proj.weight": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.9.attn.c_attn.bias": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.9.attn.c_attn.weight": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.9.attn.c_proj.bias": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.9.attn.c_proj.weight": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.9.ln_1.bias": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.9.ln_1.weight": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.9.ln_2.bias": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.9.ln_2.weight": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.9.mlp.c_fc.bias": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.9.mlp.c_fc.weight": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.9.mlp.c_proj.bias": "pytorch_model-00001-of-00004.bin",
+    "transformer.h.9.mlp.c_proj.weight": "pytorch_model-00001-of-00004.bin",
+    "transformer.ln_f.bias": "pytorch_model-00004-of-00004.bin",
+    "transformer.ln_f.weight": "pytorch_model-00004-of-00004.bin",
+    "transformer.wpe.weight": "pytorch_model-00001-of-00004.bin",
+    "transformer.wte.weight": "pytorch_model-00001-of-00004.bin"
+  }
+}

special_tokens_map.json

@@ -0,0 +1,27 @@
+{
+  "additional_special_tokens": [
+    "<|endoftext|>",
+    "<fim_prefix>",
+    "<fim_middle>",
+    "<fim_suffix>",
+    "<fim_pad>",
+    "<filename>",
+    "<gh_stars>",
+    "<issue_start>",
+    "<issue_comment>",
+    "<issue_closed>",
+    "<jupyter_start>",
+    "<jupyter_text>",
+    "<jupyter_code>",
+    "<jupyter_output>",
+    "<empty_output>",
+    "<commit_before>",
+    "<commit_msg>",
+    "<commit_after>",
+    "<reponame>"
+  ],
+  "bos_token": "<|endoftext|>",
+  "eos_token": "<|endoftext|>",
+  "pad_token": "<|pad|>",
+  "unk_token": "<|endoftext|>"
+}

tokenizer_config.json

@@ -0,0 +1,31 @@
+{
+  "add_prefix_space": false,
+  "additional_special_tokens": [
+    "<|endoftext|>",
+    "<fim_prefix>",
+    "<fim_middle>",
+    "<fim_suffix>",
+    "<fim_pad>",
+    "<filename>",
+    "<gh_stars>",
+    "<issue_start>",
+    "<issue_comment>",
+    "<issue_closed>",
+    "<jupyter_start>",
+    "<jupyter_text>",
+    "<jupyter_code>",
+    "<jupyter_output>",
+    "<empty_output>",
+    "<commit_before>",
+    "<commit_msg>",
+    "<commit_after>",
+    "<reponame>"
+  ],
+  "bos_token": "<|endoftext|>",
+  "clean_up_tokenization_spaces": true,
+  "eos_token": "<|endoftext|>",
+  "model_max_length": 1000000000000000019884624838656,
+  "tokenizer_class": "GPT2Tokenizer",
+  "unk_token": "<|endoftext|>",
+  "vocab_size": 49152
+}