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:
Task type is invalid.
- Notebooks
- Google Colab
- Kaggle
| 2026-07-25 01:57:06: orchestrator started | |
| 2026-07-25 01:57:06: final QA finished | |
| coverage: emb=1654 qa=1622 missing=32 | |
| 2026-07-25 01:57:06: assembling complete aligned dataset ... | |
| aligned6 dataset: 1647 repos (embeddings) | 22267 QA | |
| repo splits: Counter({'train': 1341, 'cr_val': 167, 'cr_test': 139}) | |
| QA by split: {'train': 18115, 'cr_test': 1896, 'cr_val': 2256} | |
| -> aligned6_embeddings.parquet + aligned6_qna.jsonl | |
| 2026-07-25 01:57:10: assembled: repos=1647 qa=22267 (was 1058 repos / 8540 qa) | |
| 2026-07-25 01:57:10: waiting for next checkpoint save to time the kill (zero wasted steps) ... | |
| 2026-07-25 02:01:17: checkpoint just saved (mtime bumped) at step841; KILLING training now to switch dataset | |
| 2026-07-25 02:01:17: training killed; supervisor will relaunch on COMPLETE dataset (1647 repos) from head.latest.pt within ~45s | |
| 2026-07-25 02:02:47: WARN: training not detected 90s after kill -- supervisor should relaunch; will self-heal | |
| 2026-07-25 02:02:47: orchestrator done | |