---
language:
  - en
license: other
library_name: transformers
pipeline_tag: text-generation
tags:
  - gguf
  - hunyuan
  - python
  - code-generation
  - code-assistant
  - instruct
  - conversational
  - causal-lm
  - full-finetune
base_model:
  - tencent/Hunyuan-0.5B-Instruct
datasets:
  - WithinUsAI/Python_GOD_Coder_Omniforge_AI_12k
  - WithinUsAI/Python_GOD_Coder_5k
  - WithinUsAI/Legend_Python_CoderV.1
model-index:
  - name: Hunyuan-PythonGOD-0.5B-GGUF
    results: []
---

# Hunyuan-PythonGOD-0.5B-GGUF

**Hunyuan-PythonGOD-0.5B-GGUF** is a compact Python-specialized coding model released in GGUF format for lightweight local inference. It is derived from a full fine-tune of `tencent/Hunyuan-0.5B-Instruct` and is aimed at code generation, Python scripting, debugging help, implementation tasks, and coding-oriented chat workflows.

This repo provides quantized GGUF builds for efficient use with llama.cpp-compatible runtimes and other GGUF-serving backends.

## Model Details

### Base Model
- **Base model:** `tencent/Hunyuan-0.5B-Instruct`
- **Architecture:** Causal decoder-only language model
- **Parameter scale:** ~0.5B
- **Specialization:** Python coding and general code-assistant behavior
- **Release format:** GGUF

### Included Files
- `Hunyuan-PythonGOD-0.5B.Q4_K_M.gguf`
- `Hunyuan-PythonGOD-0.5B.Q5_K_M.gguf`
- `Hunyuan-PythonGOD-0.5B.f16.gguf`

## Training Summary

This GGUF release is based on a **full fine-tune**, not an adapter-only export.

### Training Datasets
- `WithinUsAI/Python_GOD_Coder_Omniforge_AI_12k`
- `WithinUsAI/Python_GOD_Coder_5k`
- `WithinUsAI/Legend_Python_CoderV.1`

### Training Characteristics
- Full-parameter fine-tuning
- Python/code-oriented instruction tuning
- Exported as standard model weights before GGUF conversion
- Intended for compact coding assistance and local inference experimentation

## Intended Uses

### Good Fits
- Python function generation
- Python script writing
- Debugging assistance
- Automation script drafting
- Code-oriented local assistants
- Small-model coding experiments

### Not Intended For
- Safety-critical software deployment without review
- Autonomous execution without sandboxing
- Guaranteed bug-free or secure code generation
- Medical, legal, or financial decision support

## Quantization Notes

This repo includes multiple tradeoff points:

- **Q4_K_M**: smaller footprint, faster/lighter inference
- **Q5_K_M**: stronger quality-to-size balance
- **F16**: highest fidelity in this repo, larger memory cost

## Example llama.cpp Usage

```bash
./llama-cli -m Hunyuan-PythonGOD-0.5B.Q5_K_M.gguf -p "Write a Python function that validates an email address." -n 256