Spaces:
Running
Running
Merge branch 'main' of https://huggingface.co/spaces/mgyigit/probe3
Browse files- .gitattributes +35 -0
- Makefile +13 -0
- README.md +45 -0
- app.py +129 -0
- index.html +19 -0
- pyproject.toml +13 -0
- requirements.txt +19 -0
- style.css +28 -0
.gitattributes
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*.rar filter=lfs diff=lfs merge=lfs -text
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*.safetensors filter=lfs diff=lfs merge=lfs -text
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saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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*.tar.* filter=lfs diff=lfs merge=lfs -text
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*.tar filter=lfs diff=lfs merge=lfs -text
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Makefile
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.PHONY: style format
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style:
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python -m black --line-length 119 .
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python -m isort .
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ruff check --fix .
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quality:
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python -m black --check --line-length 119 .
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python -m isort --check-only .
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ruff check .
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README.md
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---
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title: PROBE
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emoji: 🥇
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colorFrom: green
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colorTo: indigo
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sdk: gradio
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app_file: app.py
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pinned: false
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license: gpl
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python_version: 3.8.1
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---
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# Start the configuration
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Most of the variables to change for a default leaderboard are in `src/env.py` (replace the path for your leaderboard) and `src/about.py` (for tasks).
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Results files should have the following format and be stored as json files:
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```json
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{
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"config": {
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"model_dtype": "torch.float16", # or torch.bfloat16 or 8bit or 4bit
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"model_name": "path of the model on the hub: org/model",
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"model_sha": "revision on the hub",
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},
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"results": {
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"task_name": {
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"metric_name": score,
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},
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"task_name2": {
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"metric_name": score,
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}
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}
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}
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```
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Request files are created automatically by this tool.
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If you encounter problem on the space, don't hesitate to restart it to remove the create eval-queue, eval-queue-bk, eval-results and eval-results-bk created folder.
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# Code logic for more complex edits
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You'll find
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- the main table' columns names and properties in `src/display/utils.py`
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- the logic to read all results and request files, then convert them in dataframe lines, in `src/leaderboard/read_evals.py`, and `src/populate.py`
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- the logic to allow or filter submissions in `src/submission/submit.py` and `src/submission/check_validity.py`
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app.py
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__all__ = ['block', 'make_clickable_model', 'make_clickable_user', 'get_submissions']
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import gradio as gr
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import pandas as pd
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import re
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import pandas as pd
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import os
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import json
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from src.about import *
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global data_component, filter_component
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def get_baseline_df():
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df = pd.read_csv(CSV_RESULT_PATH)
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present_columns = ["Method"] + checkbox_group.value
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df = df[present_columns]
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return df
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def add_new_eval(
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human_file,
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skempi_file,
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model_name_textbox: str,
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revision_name_textbox: str,
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benchmark_type: str,
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):
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representation_name = model_name_textbox if revision_name_textbox == '' else revision_name_textbox
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print(representation_name)
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# Save human and skempi files under ./src/data/representation_vectors using pandas
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if human_file is not None:
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human_df = pd.read_csv(human_file)
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human_df.to_csv(f"./src/data/representation_vectors/{representation_name}_human.csv", index=False)
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return None
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block = gr.Blocks()
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with block:
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gr.Markdown(
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LEADERBOARD_INTRODUCTION
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)
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with gr.Tabs(elem_classes="tab-buttons") as tabs:
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# table jmmmu bench
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with gr.TabItem("🏅 PROBE Benchmark", elem_id="probe-benchmark-tab-table", id=1):
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# selection for column part:
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checkbox_group = gr.CheckboxGroup(
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choices=TASK_INFO,
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label="Benchmark Type",
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interactive=True,
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) # user can select the evaluation dimension
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baseline_value = get_baseline_df()
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baseline_header = ["Method"] + checkbox_group.value
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baseline_datatype = ['markdown'] + ['number'] * len(checkbox_group.value)
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data_component = gr.components.Dataframe(
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value=baseline_value,
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headers=baseline_header,
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type="pandas",
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datatype=baseline_datatype,
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interactive=False,
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visible=True,
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)
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# table 5
|
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with gr.TabItem("📝 About", elem_id="probe-benchmark-tab-table", id=2):
|
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with gr.Row():
|
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gr.Markdown(LLM_BENCHMARKS_TEXT, elem_classes="markdown-text")
|
70 |
+
|
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with gr.TabItem("🚀 Submit here! ", elem_id="probe-benchmark-tab-table", id=3):
|
72 |
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with gr.Row():
|
73 |
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gr.Markdown(EVALUATION_QUEUE_TEXT, elem_classes="markdown-text")
|
74 |
+
|
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with gr.Row():
|
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gr.Markdown("# ✉️✨ Submit your model's representation files here!", elem_classes="markdown-text")
|
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with gr.Row():
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with gr.Column():
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model_name_textbox = gr.Textbox(
|
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label="Model name",
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)
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revision_name_textbox = gr.Textbox(
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label="Revision Model Name",
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)
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# Selection for benchmark type from (similartiy, family, function, affinity) to eval the representations (chekbox)
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benchmark_type = gr.CheckboxGroup(
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choices=TASK_INFO,
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label="Benchmark Type",
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interactive=True,
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)
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with gr.Column():
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human_file = gr.components.File(label="Click to Upload the representation file (csv) for Human dataset", file_count="single", type='binary')
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skempi_file = gr.components.File(label="Click to Upload the representation file (csv) for SKEMPI dataset", file_count="single", type='binary')
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96 |
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submit_button = gr.Button("Submit Eval")
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submission_result = gr.Markdown()
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submit_button.click(
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add_new_eval,
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inputs = [
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human_file,
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skempi_file,
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model_name_textbox,
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revision_name_textbox,
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benchmark_type
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],
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)
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def refresh_data():
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value = get_baseline_df()
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return value
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with gr.Row():
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data_run = gr.Button("Refresh")
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data_run.click(
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refresh_data, outputs=[data_component]
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)
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with gr.Accordion("Citation", open=False):
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122 |
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citation_button = gr.Textbox(
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value=CITATION_BUTTON_TEXT,
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label=CITATION_BUTTON_LABEL,
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elem_id="citation-button",
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show_copy_button=True,
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)
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block.launch()
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index.html
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<!doctype html>
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<html>
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<head>
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<meta charset="utf-8" />
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<meta name="viewport" content="width=device-width" />
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<title>My static Space</title>
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<link rel="stylesheet" href="style.css" />
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</head>
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<body>
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<div class="card">
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<h1>Welcome to your static Space!</h1>
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<p>You can modify this app directly by editing <i>index.html</i> in the Files and versions tab.</p>
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<p>
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Also don't forget to check the
|
15 |
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<a href="https://huggingface.co/docs/hub/spaces" target="_blank">Spaces documentation</a>.
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</p>
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</div>
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</body>
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</html>
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pyproject.toml
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[tool.ruff]
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# Enable pycodestyle (`E`) and Pyflakes (`F`) codes by default.
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select = ["E", "F"]
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ignore = ["E501"] # line too long (black is taking care of this)
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line-length = 119
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fixable = ["A", "B", "C", "D", "E", "F", "G", "I", "N", "Q", "S", "T", "W", "ANN", "ARG", "BLE", "COM", "DJ", "DTZ", "EM", "ERA", "EXE", "FBT", "ICN", "INP", "ISC", "NPY", "PD", "PGH", "PIE", "PL", "PT", "PTH", "PYI", "RET", "RSE", "RUF", "SIM", "SLF", "TCH", "TID", "TRY", "UP", "YTT"]
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+
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[tool.isort]
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profile = "black"
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line_length = 119
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[tool.black]
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line-length = 119
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requirements.txt
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APScheduler
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black
|
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datasets
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gradio
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gradio[oauth]
|
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gradio_leaderboard==0.0.9
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7 |
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gradio_client
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huggingface-hub>=0.18.0
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python-dateutil
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tqdm
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transformers
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12 |
+
tokenizers>=0.15.0
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sentencepiece
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matplotlib
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numpy
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pandas==1.1.4
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pyyaml==5.1
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scikit-learn==0.22
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scikit-multilearn==0.2.0
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style.css
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body {
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2 |
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padding: 2rem;
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font-family: -apple-system, BlinkMacSystemFont, "Arial", sans-serif;
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}
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5 |
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h1 {
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font-size: 16px;
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margin-top: 0;
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}
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p {
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color: rgb(107, 114, 128);
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13 |
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font-size: 15px;
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14 |
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margin-bottom: 10px;
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15 |
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margin-top: 5px;
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}
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17 |
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.card {
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+
max-width: 620px;
|
20 |
+
margin: 0 auto;
|
21 |
+
padding: 16px;
|
22 |
+
border: 1px solid lightgray;
|
23 |
+
border-radius: 16px;
|
24 |
+
}
|
25 |
+
|
26 |
+
.card p:last-child {
|
27 |
+
margin-bottom: 0;
|
28 |
+
}
|