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README.md

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----
-license: apache-2.0
----
+[切换到中文版本](README_zh.md) 
+
+[Switch to English Version](README.md)
+
+# Noname AI
+
+Projects related to Noname AI/Noname AI, involving AI programs aimed at generating Noname skill codes by inputting skill effects.
+
+[modelscope Online Experience](https://www.modelscope.cn/studios/huskyhong/nonameai)
+
+Due to limited computing power, the online experience version is only a lightweight CPU version with limited precision. If needed, please choose the GPU version or full version for inference.
+Fine-tuned from QWen.
+
+## Configuration Requirements
+
+To better meet usage requirements, please try to meet the following requirements:
+
+- Computer (required)
+- Hard disk storage space of 20G or more (required)
+- If using the full non-quantized version/GPU version lazy one-click package, for computers with NVIDIA graphics cards, GPU inference is used, requiring half of the graphics memory + computer physical memory (physical memory does not include virtual memory) >= 16G
+- If using the full non-quantized version/CPU version lazy one-click package, CPU inference is used, requiring memory (including virtual memory) to be as close as possible to >= 32G for computers without graphics cards
+- If using the lightweight version/GPU version lightweight lazy one-click package, for computers with NVIDIA graphics cards, GPU inference is used, requiring half of the graphics memory + computer physical memory (physical memory does not include virtual memory) >= 4G
+- If using the lightweight version/CPU version lightweight lazy one-click package, CPU inference is used, requiring memory (including virtual memory) to be as close as possible to >= 12G for computers without graphics cards
+
+## Usage
+
+### Full Model Method
+
+1. Install Python and the corresponding Python compiler.
+   - Note: Python compatible versions are 3.8, 3.9, 3.10, 3.11. Please do not install versions that are too high or too low.
+2. Enter the following command in the terminal to install the required environment:
+
+   ```bash
+   pip install -r requirements.txt
+   ```
+
+3. Run the program using the following Python code. The model will be automatically downloaded, and the code defaults to version 2.0 full version.
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+from transformers.generation import GenerationConfig
+tokenizer = AutoTokenizer.from_pretrained("huskyhong/noname-ai-v2_5", trust_remote_code=True)
+model = AutoModelForCausalLM.from_pretrained("huskyhong/noname-ai-v2_5", device_map="auto", trust_remote_code=True).eval() # Load the model using GPU
+# model = AutoModelForCausalLM.from_pretrained("huskyhong/noname-ai-v2_5", device_map="cpu", trust_remote_code=True).eval() # Load the model using CPU
+5model.generation_config = GenerationConfig.from_pretrained("huskyhong/noname-ai-v2_5", trust_remote_code=True) # You can specify different generation lengths, top_p, 和 other related hyperparameters
+# For the first generation model, replace "huskyhong/noname-ai-v2_5" with "huskyhong/noname-ai-v1". For lightweight version v2.5 model, replace "huskyhong/noname-ai-v2_5" with "huskyhong/noname-ai-v2_5-light"
+
+prompt = "请帮我编写一个技能，技能效果如下：" + input("请输入技能效果：")
+response, history = model.chat(tokenizer, prompt, history = [])
+print(response)
+
+prompt = "请帮我编写一张卡牌，卡牌效果如下：：" + input("请输入卡牌效果：")
+response, history = model.chat(tokenizer, prompt, history = [])
+print(response)
+```
+Alternatively, you can use Hugging Face's pipeline for inference.
+```python
+from transformers import pipeline, AutoTokenizer, AutoModelForCausalLM, GenerationConfig
+generator = pipeline(
+    "text-generation",
+    model="huskyhong/noname-ai-v2_5",
+    tokenizer="huskyhong/noname-ai-v2_5",
+    device=0,  # Choose GPU device. If you want to use CPU, you can set device=-1
+    trust_remote_code=True
+)
+
+prompt = "请帮我编写一个技能，技能效果如下：" + input("请输入技能效果：")
+response = generator(prompt, max_length=50, top_p=0.95)  # You can adjust parameters such as generation length, top_p as needed
+print(response[0]['generated_text'])
+
+prompt = "请帮我编写一张卡牌，卡牌效果如下：" + input("请输入卡牌效果：")
+response = generator(prompt, max_length=50, top_p=0.95)  # You can adjust parameters such as generation length, top_p as needed
+print(response[0]['generated_text'])
+```
+
+4. If automatic downloading fails, you can manually download the model files and modify "huskyhong/noname-ai-v2" to the corresponding location in the code.  
+   Download links for the second-generation model:  
+   - [v2.5 Hugging Face address (full version)](https://huggingface.co/huskyhong/noname-ai-v2_5)
+   - [v2.5 Hugging Face address (lightweight version)](https://huggingface.co/huskyhong/noname-ai-v2_5-light)
+   - [Baidu Netdisk address](https://pan.baidu.com/s/1m9RfGqnuQbRYROE_UzuG-Q?pwd=6666) Baidu Netdisk extraction code: 6666  
+   Download links for the first-generation model:
+   - [Hugging Face address](https://huggingface.co/huskyhong/noname-ai-v1)
+   - [Baidu Netdisk address](https://pan.baidu.com/s/1Ox471XuHF_gJbcPPnSZe7g?pwd=6666) Baidu Netdisk extraction code: 6666  
+Remember to choose whether to load the model using GPU or CPU, and replace `your_model_name` with your actual model path.
+
+## Lazy One-Click Package
+
+- One-click installation, no worries.  
+- Please choose the appropriate lazy one-click package according to your own configuration.  
+- [Lazy One-Click Package Baidu Netdisk Download Address (Updated to v2.5)](https://pan.baidu.com/s/1zIcRZtQv5oIdu7_abie9Vw?pwd=6666) Baidu Netdisk extraction code: 6666  
+- [Lazy One-Click Package 123 Netdisk Download Address (Updated to v2.5)](https://www.123pan.com/s/lOcnjv-pnOG3.html) 123 Netdisk extraction code: 6666  
+- Please pay attention to the version time of the lazy one-click package to ensure that the version is the latest!  
+- Lazy package related videos  
+- [Comparison of Effects of Lazy Package v2.5](https://www.bilibili.com/video/BV1KKY4e8EaC/)  
+
+## Web Version/Server Deployment
+   - Install Python  
+   - Install dependencies  
+   ```bash
+   pip install -r requirements.txt
+   ```  
+  - Install Streamlit
+   ```bash
+   pip install streamlit
+   ```
+   - Allow port 8501 on the server (can also be changed to others, corresponding to webdemo.py file)
+   - Run webdemo
+   ```bash
+   streamlit run webdemo.py
+   ```
+## Training  
+Training requires installing new dependencies:  
+```python
+pip install peft deepspeed
+```  
+Clone the project和download the v2.3 version of the model files, taking the lightweight version as an example:  
+```bash
+git lfs install
+git clone https://github.com/204313508/noname_llm.git
+git clone https://huggingface.co/huskyhong/noname-ai-v2_3-light
+cd noname_llm/finetune
+```  
+Modify the parameters required for training in the finetune script, such as model and dataset locations, then enter the following command to start training:  
+```bash
+bash finetune.sh
+```  
+Please refer to the [Fine-tuning Guide](./finetune/README.md) for detailed steps.
+   
+## Web Version/Server Example
+![webdemo1](./webdemo1.png)
+![webdemo2](./webdemo2.png)
+
+## Notes
+
+- AI generation is subject to uncontrollable factors, and the generated code does not guarantee 100% effectiveness. Bugs, redundant code, or additional special characters may still occur and require manual modification.
+- (Important) Follow AI specifications. This AI model is for learning and communication purposes only. Please do not use it for illegal or commercial purposes. The purpose of releasing this model is to encourage better learning and communication, and all related information involved in the model is public. I bear no responsibility for malicious use of this AI model.
+
+## Other Content
+
+If you have any related questions, please raise them in the official GitHub issue.
+
+## Demo Images
+These demo images are based on version 2.3 release.  
+![demo](./demo.png)
+
+
+## Sponsorship
+- Shamelessly begging for sponsorship
+![sponsor](./sponsor.jpg)

README_zh.md

@@ -0,0 +1,138 @@
+[切换到中文版本](README_zh.md) 
+
+[Switch to English Version](README.md)
+# 无名杀AI
+
+无名杀ai/无名杀AI相关项目，该项目涉及AI程序，旨在通过输入技能效果，生成无名杀技能代码。  
+[modelscope（魔搭社区）在线体验](https://www.modelscope.cn/studios/huskyhong/nonameai)  
+因为算力有限，在线体验版本仅为轻量cpu版，精度有限，如有需求请选择gpu版、完整版进行推理
+finetuned from QWen
+## 配置要求
+
+为了更好地满足使用需求，请尽可能满足以下要求:
+
+- 电脑（必须）
+- 硬盘存储空间20G以上（必须）
+- 若使用完整非量化版本/gpu版懒人一键包，对于具有 NVIDIA 显卡的电脑，采用gpu推理，要求显存 + 电脑物理内存（物理内存不包含虚拟内存）的一半 >= 16G
+- 若使用完整非量化版本/cpu版懒人一键包，采用cpu方式推理，对于无显卡的电脑，要求内存（可包含虚拟内存）尽可能满足 >= 32G
+- 若使用轻量版/gpu版轻量版懒人一键包，对于具有 NVIDIA 显卡的电脑，采用gpu推理，要求显存 + 电脑物理内存（物理内存不包含虚拟内存）的一半 >= 4G
+- 若使用轻量版/cpu版轻量版懒人一键包，采用cpu方式推理，对于无显卡的电脑，要求内存（可包含虚拟内存）尽可能满足 >= 12G
+
+## 使用方法
+### 完整模型法
+1. 安装 Python 以及相应的 Python 编译器
+  - 注意：python适配版本为3.8,3.9,3.10,3.11，请勿安装过高或过低版本
+2. 在终端（命令行）中输入以下命令安装依赖环境:
+
+   ```bash
+   pip install -r requirements.txt
+   ```
+3. 采用以下python代码运行程序，模型将会自动下载，代码默认为v2.0完整版
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+from transformers.generation import GenerationConfig
+tokenizer = AutoTokenizer.from_pretrained("huskyhong/noname-ai-v2_5", trust_remote_code=True)
+model = AutoModelForCausalLM.from_pretrained("huskyhong/noname-ai-v2_5", device_map="auto", trust_remote_code=True).eval() # 采用gpu加载模型
+# model = AutoModelForCausalLM.from_pretrained("huskyhong/noname-ai-v2_5", device_map="cpu", trust_remote_code=True).eval() # 采用cpu加载模型
+model.generation_config = GenerationConfig.from_pretrained("huskyhong/noname-ai-v2_5", trust_remote_code=True) # 可指定不同的生成长度、top_p等相关超参
+# 第一代模型请将huskyhong/noname-ai-v2_5改为huskyhong/noname-ai-v1，轻量版v2.5模型请将huskyhong/noname-ai-v2_5改为huskyhong/noname-ai-v2_5-light
+
+prompt = "请帮我编写一个技能，技能效果如下：" + input("请输入技能效果：")
+response, history = model.chat(tokenizer, prompt, history = [])
+print(response)
+
+prompt = "请帮我编写一张卡牌，卡牌效果如下：：" + input("请输入卡牌效果：")
+response, history = model.chat(tokenizer, prompt, history = [])
+print(response)
+```
+也可以采用huggingface的pipeline进行推理
+```python
+from transformers import pipeline, AutoTokenizer, AutoModelForCausalLM, GenerationConfig
+generator = pipeline(
+    "text-generation",
+    model="huskyhong/noname-ai-v2_5",
+    tokenizer="huskyhong/noname-ai-v2_5",
+    device=0,  # 选择GPU设备，如果要使用CPU，可以设置device=-1
+    trust_remote_code=True
+)
+
+prompt = "请帮我编写一个技能，技能效果如下：" + input("请输入技能效果：")
+response = generator(prompt, max_length=50, top_p=0.95)  # 可根据需要调整生成长度、top_p等超参数)
+print(response[0]['generated_text'])
+
+prompt = "请帮我编写一张卡牌，卡牌效果如下：" + input("请输入卡牌效果：")
+response = generator(prompt, max_length=50, top_p=0.95)  # 可根据需要调整生成长度、top_p等超参数
+print(response[0]['generated_text'])
+```
+
+4. 如果自动下载出错，可以手动下载模型文件，同时修改代码中的"huskyhong/noname-ai-v2"为相应位置  
+      第二代模型下载地址:
+   - [v2.5版本huggingface地址（完整版）](https://huggingface.co/huskyhong/noname-ai-v2_5)
+   - [v2.5版本huggingface地址（轻量版）](https://huggingface.co/huskyhong/noname-ai-v2_5-light)
+   - [百度网盘地址](https://pan.baidu.com/s/1m9RfGqnuQbRYROE_UzuG-Q?pwd=6666) 百度网盘提取码：6666   
+     第一代模型下载地址:
+   - [huggingface地址](https://huggingface.co/huskyhong/noname-ai-v1)
+   - [百度网盘地址](https://pan.baidu.com/s/1Ox471XuHF_gJbcPPnSZe7g?pwd=6666) 百度网盘提取码：6666 
+记得选择采用gpu加载模型还是cpu加载模型，然后把 `your_model_name` 替换为你实际的模型路径。
+
+## 懒人一键包
+- 一键安装，无需烦恼
+- 请根据自身配置选择合适的懒人一键包
+- [懒人一键包百度网盘下载地址（已更新v2.5）](https://pan.baidu.com/s/1zIcRZtQv5oIdu7_abie9Vw?pwd=6666) 百度网盘提取码：6666
+- [懒人���键包123网盘下载地址（已更新v2.5）](https://www.123pan.com/s/lOcnjv-pnOG3.html) 123网盘提取码:6666
+- 请注意懒人一键包版本时间，确保版本为最新版！
+- 懒人包相关视频
+- [懒人包v2.5版效果对比]([https://www.bilibili.com/video/BV1KKY4e8EaC]
+## 网页版/服务器部署
+   - 安装 Python 
+   - 安装依赖环境
+   ```bash
+   pip install -r requirements.txt
+   ```
+  - 安装streamlit
+   ```bash
+   pip install streamlit
+   ```
+   - 服务器放行8501端口（也可自行改成其他，需要和webdemo.py文件中对应）
+   - 运行webdemo
+   ```bash
+   streamlit run webdemo.py
+   ```
+
+## 训练/微调  
+训练/微调需要安装新的依赖项
+```python
+pip install peft deepspeed
+```
+克隆该项目，并下载v2.3版本的模型文件，以轻量版为例：
+```bash
+git lfs install
+git clone https://github.com/204313508/noname_llm.git
+git clone https://huggingface.co/huskyhong/noname-ai-v2_3-light
+cd noname_llm/finetune
+```  
+修改finetune.sh中训练所需参数，模型、数据集位置等信息，之后输入以下命令开始训练  
+```bash
+bash finetune.sh
+```
+详细步骤请参考[微调说明](./finetune/README.md)
+
+## 网页版/服务器示例
+![webdemo1](./webdemo1.png)
+![webdemo2](./webdemo2.png)
+## 注意事项
+
+- AI生成受不可控因素影响，生成的代码不保证100%有效，仍可能出现bug、冗余代码或额外特殊符号等，需要人工修改。
+- （重要）遵循AI规范，本AI模型仅用于学习交流使用，请勿用于不法用途以及商业用途。本人发布该模型初衷是希望大家更好地学习和交流，模型涉及的所有相关信息都是公开的。对于恶意使用本AI模型的，本人概不负责。
+
+## 其他内容
+
+如果有相关问题，请在GitHub官方的issue中提出。
+
+## 演示图片
+该演示图片基于v2.3发布  
+![demo1](./demo.png)
+
+## 赞助
+- 厚颜无耻的求一个赞助
+![sponsor](./sponsor.jpg)