Spaces:
Running
Running
Commit History
-
Update backend/app/data/sample_results.json
Verified signature64cf512
-
Fix dataset IDs to match actual HuggingFace repo names
Update bcic-2a → bcic2a, physionet-mi → physionet, chb-mit → chbmit in both the backend benchmark registry and frontend dataset URLs.af3dd25
-
Add HF eval-results benchmark registry and API endpoint
- Add canonical EEG_BENCHMARKS registry (8 datasets) in config/benchmarks.py - Add GET /api/benchmarks endpoint for benchmark metadata - Refactor leaderboard transform_data to loop over registry instead of hardcoding - Extract _build_entry_id helper for consistent unique ID generation - Add push_eval_yaml.py script to register benchmarks on HF Hub - Add pyyaml dependency6f5cc9b
-
Fix server 500 error and replace HF logos with eegdash branding
- Add local sample data fallback when braindecode/contents HF dataset is unavailable (backend/app/data/sample_results.json with 20 entries) - Make fastapi-cache2 imports robust with graceful no-op fallback - Replace Hugging Face SVG logo with eegdash brain+EEG wave logo - Generate new favicon PNGs (32px, 256px) from eegdash SVG - Add missing http-proxy-middleware dependency to frontend package.json - Update OG URL to new Space name (OpenEEGBench) - Update AuthContainer to remove HF-specific branding text5b89071 -
Align frontend and backend with adapter_finetuning paper
Replace all LLM-specific references with real EEG benchmark data: - 8 EEG datasets (BCIC-2a, PhysioNet, ISRUC, TUAB, TUEV, CHB-MIT, FACED, SEED-V) - 7 adapter methods (LoRA, IA3, AdaLoRA, DoRA, OFT, Probe, Full Fine-tune) - 7 foundation models (LaBraM, EEGPT, BIOT, BENDR, SignalJEPA, CBraMod, REVE) - Remove official providers, MoE, flagged, merged features - Update params from billions to millions scale - Add real citations and dataset descriptions from the paper5763bf2 -
Migrate from Gradio to React + FastAPI architecture
Replace the old Gradio-based leaderboard with a React frontend and FastAPI backend, adapted from the Open LLM Leaderboard codebase for EEG model evaluation. Backend: FastAPI app with leaderboard, model submission, and voting endpoints. Frontend: React + MUI with leaderboard table, filters, model submission, voting, about page, and citations. Infrastructure: Dockerfile, docker-compose, and env configuration for HF Spaces.ee472e7