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import os | |
os.system("wget https://raw.githubusercontent.com/Weyaxi/scrape-open-llm-leaderboard/main/openllm.py") | |
from huggingface_hub import CommitOperationAdd, create_commit, HfApi, HfFileSystem, login | |
from huggingface_hub.utils import RepositoryNotFoundError as deneme | |
from openllm import * | |
import gradio as gr | |
import requests | |
import pandas as pd | |
api = HfApi() | |
fs = HfFileSystem() | |
data = get_json_format_data() | |
finished_models = get_datas(data) | |
df = pd.DataFrame(finished_models) | |
def search(df, value): | |
result_df = df[df["Model"] == value] | |
return result_df.iloc[0].to_dict() if not result_df.empty else None | |
def get_details_url(repo): | |
author, model = repo.split("/") | |
return f"https://huggingface.co/datasets/open-llm-leaderboard/details_{author}__{model}" | |
def get_eval_results(repo): | |
results = search(df, repo) | |
text = f""" | |
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard) | |
Detailed results can be found [here]({get_details_url(repo)}) | |
| Metric | Value | | |
|-----------------------|---------------------------| | |
| Avg. | {results['Average ⬆️']} | | |
| ARC (25-shot) | {results['ARC']} | | |
| HellaSwag (10-shot) | {results['HellaSwag']} | | |
| MMLU (5-shot) | {results['MMLU']} | | |
| TruthfulQA (0-shot) | {results['TruthfulQA']} | | |
| Winogrande (5-shot) | {results['Winogrande']} | | |
| GSM8K (5-shot) | {results['GSM8K']} | | |
""" | |
return text | |
desc = """ | |
This is an automated PR created with https://huggingface.co/spaces/Weyaxi/open-llm-leaderboard-results-pr | |
The purpose of this PR is to add evaluation results from the Open LLM Leaderboard to your model card. | |
If you encounter any issues, please report them to https://huggingface.co/spaces/Weyaxi/open-llm-leaderboard-results-pr/discussions | |
""" | |
def commit(hf_token, repo): | |
login(hf_token) | |
try: | |
try: # check if there is a readme already | |
readme_text = fs.read_text(f"{repo}/README.md") + get_eval_results(repo) | |
except: | |
readme_text = get_eval_results(repo) | |
liste = [CommitOperationAdd(path_in_repo="README.md", path_or_fileobj=readme_text.encode())] | |
commit = (create_commit(repo_id=repo, operations=liste, commit_message=f"Adding Evaluation Results", commit_description=desc, repo_type="model", create_pr=True).__dict__['pr_url']) | |
return commit | |
except Exception as e: # unexpected error | |
return e | |
demo = gr.Interface(fn=commit, inputs=["text", "text"], outputs="text") | |
demo.launch() |