- README rewritten with judging-criteria quick-map, links table, real plot embedded
- BLOG_POST: marketing copy with honest training framing
- training_curves.png: 4-panel dashboard from real metrics.json (2000 datapoints)
- metrics.json: full per-step training history pulled from model repo
- scripts/plot_from_metrics.py: regenerates curves from metrics.json
- scripts/plot_from_logs.py: scrape-from-logs fallback (real datapoints only)
- training/train.py: incremental upload of curves + checkpoints during training
- openenv.yaml: port 8000 -> 7860 (matches Dockerfile + HF Space)
- removed: FINAL.md, WINDOWS_SETUP.md (extra docs not needed for judging)
optimize for hackathon time budget: 256 tokens, 200-step checkpoints