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import json
import gradio as gr
import pandas as pd
from huggingface_hub import HfFileSystem
RESULTS_DATASET_ID = "datasets/open-llm-leaderboard/results"
fs = HfFileSystem()
def fetch_result_paths():
paths = fs.glob(f"{RESULTS_DATASET_ID}/**/**/*.json")
return paths
def filter_latest_result_path_per_model(paths):
from collections import defaultdict
d = defaultdict(list)
for path in paths:
model_id, _ = path[len(RESULTS_DATASET_ID) +1:].rsplit("/", 1)
d[model_id].append(path)
return {model_id: max(paths) for model_id, paths in d.items()}
def get_result_path_from_model(model_id, result_path_per_model):
return result_path_per_model[model_id]
def load_result(result_path) -> pd.DataFrame:
with fs.open(result_path, "r") as f:
data = json.load(f)
model_name = data.get("model_name", "Model")
df = pd.json_normalize([data])
return df.iloc[0].rename_axis("Parameters").rename(model_name).to_frame().reset_index()
def render_result(model_id):
result_path = get_result_path_from_model(model_id, latest_result_path_per_model)
return load_result(result_path)
# if __name__ == "__main__":
latest_result_path_per_model = filter_latest_result_path_per_model(fetch_result_paths())
with gr.Blocks(fill_height=True) as demo:
gr.HTML("<h1 style='text-align: center;'>Results of the 🤗 Open LLM Leaderboard</h1>")
gr.HTML("<h3 style='text-align: center;'>Select a result to load</h3>")
model_id = gr.Dropdown(choices=list(latest_result_path_per_model.keys()), label="Results")
load_btn = gr.Button("Load")
result = gr.Dataframe(label="Result")
load_btn.click(
fn=render_result,
inputs=model_id,
outputs=result,
)
demo.launch()
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