Instructions to use moncefem/memory-lora-gemma4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use moncefem/memory-lora-gemma4 with PEFT:
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- Notebooks
- Google Colab
- Kaggle
Commit History
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Clean the model mirror
Removes ~11.6GB of weights that should not be published: - sixview_v1/v2 checkpoints. sixview_v2 is the pre-standardisation head that scored WORSE than applying no adapter (and worse than random noise); leaving it downloadable invites someone to use it. Their metrics.jsonl stay for provenance. - duplicate all_lora/head.best.pt (same bytes as all_lora_best_cpt.pth) and a stray h200_best/ copy. - 49 files of snapshot_download bookkeeping under data/**/.cache/. Keeps the two checkpoints worth having: all_lora_best_cpt.pth (merged corpus, best) and h200_run/head.best.pt (prose-only, fallback). Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>930bb27 -
Push ALL raw datasets: commitpack (9 langs), RepoPeftBench/code2lora, combined corpora
moncefem +1: Claude Opus 4.8Adds the full raw training corpora (~9.5GB) previously kept local-only. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>cd50fed