Spaces:
Runtime error
Runtime error
| import os | |
| from huggingface_hub import CommitOperationAdd, create_commit, RepoUrl | |
| from huggingface_hub import EvalResult, ModelCard | |
| from huggingface_hub.repocard_data import eval_results_to_model_index | |
| import time | |
| from pytablewriter import MarkdownTableWriter | |
| import gradio as gr | |
| from openllm import get_json_format_data, get_datas | |
| import pandas as pd | |
| BOT_HF_TOKEN = os.getenv('BOT_HF_TOKEN') | |
| data = get_json_format_data() | |
| finished_models = get_datas(data) | |
| df = pd.DataFrame(finished_models) | |
| 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 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_query_url(repo): | |
| return f"https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query={repo}" | |
| def get_task_summary(results): | |
| return { | |
| "IFEval": | |
| {"dataset_type":"HuggingFaceH4/ifeval", | |
| "dataset_name":"IFEval (0-Shot)", | |
| "metric_type": "inst_level_strict_acc and prompt_level_strict_acc", | |
| "metric_value":results["IFEval"], | |
| "dataset_config": None, # don't know | |
| "dataset_split": None, # don't know | |
| "dataset_revision":None, | |
| "dataset_args":{"num_few_shot": 0}, | |
| "metric_name":"strict accuracy" | |
| }, | |
| "BBH": | |
| {"dataset_type":"BBH", | |
| "dataset_name":"BBH (3-Shot)", | |
| "metric_type":"acc_norm", | |
| "metric_value":results["BBH"], | |
| "dataset_config": None, # don't know | |
| "dataset_split": None, # don't know | |
| "dataset_revision":None, | |
| "dataset_args":{"num_few_shot": 3}, | |
| "metric_name":"normalized accuracy" | |
| }, | |
| "MATH Lvl 5": | |
| { | |
| "dataset_type":"hendrycks/competition_math", | |
| "dataset_name":"MATH Lvl 5 (4-Shot)", | |
| "metric_type":"exact_match", | |
| "metric_value":results["MATH Lvl 5"], | |
| "dataset_config": None, # don't know | |
| "dataset_split": None, # don't know | |
| "dataset_revision":None, | |
| "dataset_args":{"num_few_shot": 4}, | |
| "metric_name":"exact match" | |
| }, | |
| "GPQA": | |
| { | |
| "dataset_type":"Idavidrein/gpqa", | |
| "dataset_name":"GPQA (0-shot)", | |
| "metric_type":"acc_norm", | |
| "metric_value":results["GPQA"], | |
| "dataset_config": None, # don't know | |
| "dataset_split": None, # don't know | |
| "dataset_revision":None, | |
| "dataset_args":{"num_few_shot": 0}, | |
| "metric_name":"acc_norm" | |
| }, | |
| "MuSR": | |
| { | |
| "dataset_type":"TAUR-Lab/MuSR", | |
| "dataset_name":"MuSR (0-shot)", | |
| "metric_type":"acc_norm", | |
| "metric_value":results["MUSR"], | |
| "dataset_config": None, # don't know | |
| "dataset_split": None, # don't know | |
| "dataset_args":{"num_few_shot": 0}, | |
| "metric_name":"acc_norm" | |
| }, | |
| "MMLU-PRO": | |
| { | |
| "dataset_type":"TIGER-Lab/MMLU-Pro", | |
| "dataset_name":"MMLU-PRO (5-shot)", | |
| "metric_type":"acc", | |
| "metric_value":results["MMLU-PRO"], | |
| "dataset_config":"main", | |
| "dataset_split":"test", | |
| "dataset_args":{"num_few_shot": 5}, | |
| "metric_name":"accuracy" | |
| } | |
| } | |
| def get_eval_results(repo): | |
| results = search(df, repo) | |
| task_summary = get_task_summary(results) | |
| md_writer = MarkdownTableWriter() | |
| md_writer.headers = ["Metric", "Value"] | |
| md_writer.value_matrix = [["Avg.", results['Average ⬆️']]] + [[v["dataset_name"], v["metric_value"]] for v in task_summary.values()] | |
| text = f""" | |
| # [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard) | |
| Detailed results can be found [here]({get_details_url(repo)}) | |
| {md_writer.dumps()} | |
| """ | |
| return text | |
| def get_edited_yaml_readme(repo, token: str | None): | |
| card = ModelCard.load(repo, token=token) | |
| results = search(df, repo) | |
| common = {"task_type": 'text-generation', "task_name": 'Text Generation', "source_name": "Open LLM Leaderboard", "source_url": f"https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query={repo}"} | |
| tasks_results = get_task_summary(results) | |
| if not card.data['eval_results']: # No results reported yet, we initialize the metadata | |
| card.data["model-index"] = eval_results_to_model_index(repo.split('/')[1], [EvalResult(**task, **common) for task in tasks_results.values()]) | |
| else: # We add the new evaluations | |
| for task in tasks_results.values(): | |
| cur_result = EvalResult(**task, **common) | |
| if any(result.is_equal_except_value(cur_result) for result in card.data['eval_results']): | |
| continue | |
| card.data['eval_results'].append(cur_result) | |
| return str(card) | |
| def commit(repo, pr_number=None, message="Adding Evaluation Results", oauth_token: gr.OAuthToken | None = None): # specify pr number if you want to edit it, don't if you don't want | |
| global df | |
| data = get_json_format_data() | |
| finished_models = get_datas(data) | |
| df = pd.DataFrame(finished_models) | |
| if not oauth_token: | |
| raise gr.Warning("You are not logged in. Click on 'Sign in with Huggingface' to log in.") | |
| else: | |
| token = oauth_token | |
| if repo.startswith("https://huggingface.co/"): | |
| try: | |
| repo = RepoUrl(repo).repo_id | |
| except Exception: | |
| raise gr.Error(f"Not a valid repo id: {str(repo)}") | |
| edited = {"revision": f"refs/pr/{pr_number}"} if pr_number else {"create_pr": True} | |
| try: | |
| try: # check if there is a readme already | |
| readme_text = get_edited_yaml_readme(repo, token=token) + get_eval_results(repo) | |
| except Exception as e: | |
| if "Repo card metadata block was not found." in str(e): # There is no readme | |
| readme_text = get_edited_yaml_readme(repo, token=token) | |
| else: | |
| print(f"Something went wrong: {e}") | |
| liste = [CommitOperationAdd(path_in_repo="README.md", path_or_fileobj=readme_text.encode())] | |
| commit = (create_commit(repo_id=repo, token=token, operations=liste, commit_message=message, commit_description=desc, repo_type="model", **edited).pr_url) | |
| return commit | |
| except Exception as e: | |
| if "Discussions are disabled for this repo" in str(e): | |
| return "Discussions disabled" | |
| elif "Cannot access gated repo" in str(e): | |
| return "Gated repo" | |
| elif "Repository Not Found" in str(e): | |
| return "Repository Not Found" | |
| else: | |
| return e |