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- Pythonified-Llama-3.2-3B-Instruct-f16.gguf +3 -0
- Pythonified-Llama-3.2-3B-Instruct-q3_k_m.gguf +3 -0
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- Pythonified-Llama-3.2-3B-Instruct-q5_k_m.gguf +3 -0
- Pythonified-Llama-3.2-3B-Instruct-q6_k.gguf +3 -0
- Pythonified-Llama-3.2-3B-Instruct-q8_0.gguf +3 -0
- README.md +79 -0
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README.md
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---
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base_model: meta-llama/Llama-3.2-3B-Instruct
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library_name: gguf
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pipeline_tag: text-generation
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language: en
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license: apache-2.0
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tags:
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- gguf
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- quantized
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- llama.cpp
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- pythonified-llama-3.2-3b-instruct
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model_type: llama
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quantized_by: theprint
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---
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# Pythonified-Llama-3.2-3B-Instruct - GGUF Quantized
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Quantized GGUF versions of [Pythonified-Llama-3.2-3B-Instruct](https://huggingface.co/theprint/Pythonified-Llama-3.2-3B-Instruct) for use with llama.cpp and other GGUF-compatible inference engines.
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## Original Model
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- **Base model:** [meta-llama/Llama-3.2-3B-Instruct](https://huggingface.co/meta-llama/Llama-3.2-3B-Instruct)
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- **Fine-tuned model:** [theprint/Pythonified-Llama-3.2-3B-Instruct](https://huggingface.co/theprint/Pythonified-Llama-3.2-3B-Instruct)
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- **Quantized by:** theprint
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## Available Quantizations
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- `Pythonified-Llama-3.2-3B-Instruct-f16.gguf` (6135.6 MB) - 16-bit float (original precision, largest file)
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- `Pythonified-Llama-3.2-3B-Instruct-q3_k_m.gguf` (1609.0 MB) - 3-bit quantization (medium quality)
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- `Pythonified-Llama-3.2-3B-Instruct-q4_k_m.gguf` (1925.8 MB) - 4-bit quantization (medium, recommended for most use cases)
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- `Pythonified-Llama-3.2-3B-Instruct-q5_k_m.gguf` (2214.6 MB) - 5-bit quantization (medium, good quality)
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- `Pythonified-Llama-3.2-3B-Instruct-q6_k.gguf` (2521.4 MB) - 6-bit quantization (high quality)
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- `Pythonified-Llama-3.2-3B-Instruct-q8_0.gguf` (3263.4 MB) - 8-bit quantization (very high quality)
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## Usage
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### With llama.cpp
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```bash
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# Download recommended quantization
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wget https://huggingface.co/theprint/Pythonified-Llama-3.2-3B-Instruct-GGUF/resolve/main/Pythonified-Llama-3.2-3B-Instruct-q4_k_m.gguf
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# Run inference
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./llama.cpp/main -m Pythonified-Llama-3.2-3B-Instruct-q4_k_m.gguf \
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-p "Your prompt here" \
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-n 256 \
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--temp 0.7 \
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--top-p 0.9
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```
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### With other GGUF tools
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These files are compatible with:
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- [llama.cpp](https://github.com/ggerganov/llama.cpp)
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- [Ollama](https://ollama.ai/) (import as custom model)
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- [KoboldCpp](https://github.com/LostRuins/koboldcpp)
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- [text-generation-webui](https://github.com/oobabooga/text-generation-webui)
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## Quantization Info
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**Recommended:** `q4_k_m` provides the best balance of size, speed, and quality for most use cases.
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**For maximum quality:** Use `q8_0` or `f16`
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**For maximum speed/smallest size:** Use `q3_k_m` or `q4_k_s`
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## License
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apache-2.0
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## Citation
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```bibtex
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@misc{pythonified_llama_3.2_3b_instruct_gguf,
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title={Pythonified-Llama-3.2-3B-Instruct GGUF Quantized Models},
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author={theprint},
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year={2025},
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publisher={Hugging Face},
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url={https://huggingface.co/theprint/Pythonified-Llama-3.2-3B-Instruct-GGUF}
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}
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```
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