LL-Square/CodeForge-TinyLlama1.1B-Instruct

1---2base_model: TinyLlama/TinyLlama-1.1B-Chat-v1.03library_name: peft4pipeline_tag: text-generation5tags:6- base_model:adapter:TinyLlama/TinyLlama-1.1B-Chat-v1.07- lora8- transformers9license: apache-2.010datasets:11- LL-Square/CodeForge-TinyLlama1.1B-Instruct12language:13- en14---15 16# CodeForge-Instruct17 18Lightweight repository for preparing, training, and uploading small instruct-style models and LoRA adapters.19 20This project contains simple scripts to train a model (`train.py`), run inference (`main.py`), configure logging (`logging_setup.py`), and upload artifacts (`upload.py`). A small sample dataset is included as `sample.jsonl`.21 22## Data format23 24The dataset expects newline-delimited JSON (`.jsonl`) where each line is an object with at least `prompt` and `response` (or `instruction`/`output`) fields. Example (`sample.jsonl`):25 26```jsonl27{"prompt": "Summarize the following text:", "response": "A short summary."}28```29 30Adjust `train.py` to match your field names if needed.31 32## Usage33 34Training (example):35 36```bash37python train.py --data sample.jsonl --output-dir ./checkpoints --epochs 3 --batch-size 838```39 40Run inference/demo:41 42```bash43python main.py --model ./checkpoints/latest44```45 46Upload artifacts (example):47 48```bash49python upload.py --model ./checkpoints/latest --dest hub-or-bucket50```51 52See individual scripts for additional flags and configuration.53 54## Logging55 56The repository centralizes logging in `logging_setup.py`; import and call `setup_logging()` from other scripts to get consistent formatting and levels.57 58## Development59 60- Run linters/formatters as you prefer (e.g. `black`, `ruff`).61- Add tests under a `tests/` folder if you expand behavior.62 63## Contributing64 65Open issues or PRs with clear reproduction steps. Keep changes minimal and scoped.66 67## License68 69This repository does not include a license file. Add a `LICENSE` if you plan to publish.70 71### Framework versions72 73- PEFT 0.18.174- 75---76If you'd like, I can:77- add a `requirements.txt` with pinned versions,78- add CLI argument parsing examples to `train.py` and `main.py`, or79- create a short CONTRIBUTING guide.