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Model: gss1147/Hunyuan-PythonGOD-0.5B-GGUF Source: Original Platform
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language:
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- en
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license: other
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library_name: transformers
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pipeline_tag: text-generation
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tags:
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- gguf
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- hunyuan
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- python
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- code-generation
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- code-assistant
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- instruct
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- conversational
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- causal-lm
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- full-finetune
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base_model:
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- tencent/Hunyuan-0.5B-Instruct
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datasets:
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- WithinUsAI/Python_GOD_Coder_Omniforge_AI_12k
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- WithinUsAI/Python_GOD_Coder_5k
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- WithinUsAI/Legend_Python_CoderV.1
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model-index:
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- name: Hunyuan-PythonGOD-0.5B-GGUF
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results: []
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---
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# Hunyuan-PythonGOD-0.5B-GGUF
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**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.
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This repo provides quantized GGUF builds for efficient use with llama.cpp-compatible runtimes and other GGUF-serving backends.
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## Model Details
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### Base Model
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- **Base model:** `tencent/Hunyuan-0.5B-Instruct`
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- **Architecture:** Causal decoder-only language model
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- **Parameter scale:** ~0.5B
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- **Specialization:** Python coding and general code-assistant behavior
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- **Release format:** GGUF
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### Included Files
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- `Hunyuan-PythonGOD-0.5B.Q4_K_M.gguf`
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- `Hunyuan-PythonGOD-0.5B.Q5_K_M.gguf`
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- `Hunyuan-PythonGOD-0.5B.f16.gguf`
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## Training Summary
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This GGUF release is based on a **full fine-tune**, not an adapter-only export.
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### Training Datasets
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- `WithinUsAI/Python_GOD_Coder_Omniforge_AI_12k`
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- `WithinUsAI/Python_GOD_Coder_5k`
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- `WithinUsAI/Legend_Python_CoderV.1`
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### Training Characteristics
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- Full-parameter fine-tuning
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- Python/code-oriented instruction tuning
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- Exported as standard model weights before GGUF conversion
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- Intended for compact coding assistance and local inference experimentation
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## Intended Uses
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### Good Fits
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- Python function generation
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- Python script writing
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- Debugging assistance
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- Automation script drafting
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- Code-oriented local assistants
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- Small-model coding experiments
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### Not Intended For
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- Safety-critical software deployment without review
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- Autonomous execution without sandboxing
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- Guaranteed bug-free or secure code generation
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- Medical, legal, or financial decision support
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## Quantization Notes
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This repo includes multiple tradeoff points:
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- **Q4_K_M**: smaller footprint, faster/lighter inference
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- **Q5_K_M**: stronger quality-to-size balance
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- **F16**: highest fidelity in this repo, larger memory cost
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## Example llama.cpp Usage
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```bash
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./llama-cli -m Hunyuan-PythonGOD-0.5B.Q5_K_M.gguf -p "Write a Python function that validates an email address." -n 256
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