File size: 3,114 Bytes
4980cc4 52c8e55 4980cc4 52c8e55 4980cc4 52c8e55 4980cc4 52c8e55 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 | ---
license: apache-2.0
base_model: Qwen/Qwen2.5-0.5B-Instruct
tags:
- gguf
- python
- code-generation
- qwen2.5
---
# PyCoder
PyCoder is a Qwen2.5-0.5B-Instruct fine-tune for Python code generation. This repository includes the merged model in Q8_0 GGUF format, an Ollama Modelfile, a small Ollama API client, and the source scripts used for training.
## Use with Ollama
The quickest option is to install [Ollama](https://ollama.com) and run:
```powershell
ollama run hf.co/Safeeq/pycoder-gguf:Q8_0
```
To download the files and create a local Ollama model instead:
```powershell
hf download Safeeq/pycoder-gguf --local-dir pycoder-gguf
cd pycoder-gguf
ollama create pycoder -f Modelfile
ollama run pycoder
```
The `hf` command is provided by `huggingface_hub` (`pip install huggingface_hub`). Alternatively, download `pycoder-q8_0.gguf` and `Modelfile` from the Files and versions tab, keep them in the same directory, and run the `ollama create` command there.
## Use the Python helper
The included [run_pycoder.py](run_pycoder.py) sends a prompt to a local Ollama server. First create or run the `pycoder` model using the steps above, then run:
```powershell
python run_pycoder.py "Write a function that reverses a string"
```
The helper uses only the Python standard library. Ollama must be installed and running locally.
## Model behavior and limitations
- Intended for generating Python code. For unrelated requests it is trained to return `# ERROR: Only Python code requests are supported.`
- This behavior is learned, not a security boundary; prompts can still produce other content.
- This is a small 0.5B-parameter model. Outputs can be incorrect, incomplete, or invalid Python, and no formal benchmark results are provided here.
- Review and test all generated code. Do not run untrusted output directly; use an isolated environment when executing generated code.
## Training
The model was fine-tuned from [Qwen/Qwen2.5-0.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-0.5B-Instruct) with LoRA. `make_dataset.py` prepares examples based on `iamtarun/python_code_instructions_18k_alpaca` plus off-topic refusal examples. The training scripts and dependencies are included for reference; training requires a compatible environment and hardware. The generated `data.jsonl`, intermediate checkpoints, and merged full-precision model are not included.
## Files
- `pycoder-q8_0.gguf`: quantized model weights.
- `Modelfile`: Ollama configuration for the local GGUF.
- `run_pycoder.py`: small client for the local Ollama API.
- `common.py`, `make_dataset.py`, `train.py`, `merge.py`, `test_model.py`: training and testing source.
- `requirements.txt`: dependencies for the training scripts and upload helper.
- `LICENSE`: license terms.
## License
The files in this repository are provided under the Apache License 2.0. The model is based on [Qwen/Qwen2.5-0.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-0.5B-Instruct); review the upstream model and dataset terms when redistributing or using their materials.
|