90 lines
2.6 KiB
Markdown
90 lines
2.6 KiB
Markdown
---
|
|
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 |