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
| # Independent batch2 pipeline: wait for the novel-repo CPU build to finish, then | |
| # run the ENHANCED QA pass on exactly those repos. Never touches training. | |
| # Leaves everything staged for a next-day assemble (does NOT re-assemble aligned6). | |
| set -u | |
| cd /Users/moncif/gemma4-hack | |
| BL=runs/build_batch2.log | |
| QL=runs/qa_batch2.log | |
| OL=runs/batch2_orchestrator.log | |
| log(){ echo "$(date '+%F %T'): $*" >> "$OL"; } | |
| log "batch2 orchestrator started; waiting for build to finish" | |
| # wait for the build process to end | |
| while pgrep -f "build_repo_multiview.py --repos-file data/batch2_novel_repos.txt" >/dev/null 2>&1; do | |
| sleep 30 | |
| done | |
| log "build finished: $(grep -oE 'Done\. [0-9]+ repos.*' "$BL" | tail -1)" | |
| # run enhanced QA on just the novel batch repos (resume-safe, appends to main qna) | |
| log "launching enhanced QA (debug/security/perf/concurrency/migration)" | |
| ./venv/bin/python scripts/generate_repo_scoped_qa_v2.py \ | |
| --sources data/docs/multiview_sources.jsonl \ | |
| --only-repos data/batch2_novel_repos.txt \ | |
| --model google/gemma-4-31b-it --workers 10 >> "$QL" 2>&1 | |
| log "enhanced QA done: $(grep -oE 'Done\. [0-9]+ novel repos.*' "$QL" | tail -1)" | |
| log "batch2 dataset READY for next-day assemble (novel repos in main pool; enhanced QA appended)" | |