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| import gradio as gr | |
| import pandas as pd | |
| import os | |
| from huggingface_hub import snapshot_download | |
| # clone / pull the lmeh eval data | |
| TOKEN = os.environ.get("TOKEN", None) | |
| RESULTS_REPO = f"lukecq/SeaExam-results" | |
| CACHE_PATH=os.getenv("HF_HOME", ".") | |
| EVAL_RESULTS_PATH = os.path.join(CACHE_PATH, "eval-results") | |
| print(EVAL_RESULTS_PATH) | |
| snapshot_download( | |
| repo_id=RESULTS_REPO, local_dir=EVAL_RESULTS_PATH, repo_type="dataset", | |
| token=TOKEN | |
| ) | |
| # Load the CSV file | |
| def load_csv(file_path): | |
| data = pd.read_csv(file_path) | |
| return data | |
| # Example path to your CSV file | |
| csv_path = f'{EVAL_RESULTS_PATH}/SeaExam_results_0419.csv' | |
| data = load_csv(csv_path) | |
| def show_data(): | |
| return data | |
| iface = gr.Interface(fn=show_data, inputs = None, outputs="dataframe", title="SeaExam Leaderboard", | |
| description="Leaderboard for the SeaExam competition.") | |
| iface.launch() | |