---
base_model: TinyLlama/TinyLlama-1.1B-Chat-v1.0
library_name: peft
pipeline_tag: text-generation
tags:
- base_model:adapter:TinyLlama/TinyLlama-1.1B-Chat-v1.0
- lora
- transformers
license: apache-2.0
datasets:
- LL-Square/CodeForge-TinyLlama1.1B-Instruct
language:
- en
---

# CodeForge-Instruct

Lightweight repository for preparing, training, and uploading small instruct-style models and LoRA adapters.

This 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`.

## Data format

The 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`):

```jsonl
{"prompt": "Summarize the following text:", "response": "A short summary."}
```

Adjust `train.py` to match your field names if needed.

## Usage

Training (example):

```bash
python train.py --data sample.jsonl --output-dir ./checkpoints --epochs 3 --batch-size 8
```

Run inference/demo:

```bash
python main.py --model ./checkpoints/latest
```

Upload artifacts (example):

```bash
python upload.py --model ./checkpoints/latest --dest hub-or-bucket
```

See individual scripts for additional flags and configuration.

## Logging

The repository centralizes logging in `logging_setup.py`; import and call `setup_logging()` from other scripts to get consistent formatting and levels.

## Development

- Run linters/formatters as you prefer (e.g. `black`, `ruff`).
- Add tests under a `tests/` folder if you expand behavior.

## Contributing

Open issues or PRs with clear reproduction steps. Keep changes minimal and scoped.

## License

This repository does not include a license file. Add a `LICENSE` if you plan to publish.

### Framework versions

- PEFT 0.18.1
- 
---
If you'd like, I can:
- add a `requirements.txt` with pinned versions,
- add CLI argument parsing examples to `train.py` and `main.py`, or
- create a short CONTRIBUTING guide.