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README.md

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+---
+base_model: google/gemma-3-1b-it
+library_name: gguf
+pipeline_tag: text-generation
+language: en
+license: mit
+tags:
+- gguf
+- quantized
+- llama.cpp
+- gemma3-python-22k-1b
+model_type: llama
+quantized_by: theprint
+---
+# Gemma3-Python-22k-1B - GGUF Quantized
+
+Quantized GGUF versions of [Gemma3-Python-22k-1B](https://huggingface.co/theprint/Gemma3-Python-22k-1B) for use with llama.cpp and other GGUF-compatible inference engines.
+
+## Original Model
+
+- **Base model:** [google/gemma-3-1b-it](https://huggingface.co/google/gemma-3-1b-it)
+- **Fine-tuned model:** [theprint/Gemma3-Python-22k-1B](https://huggingface.co/theprint/Gemma3-Python-22k-1B)
+- **Quantized by:** theprint
+
+## Available Quantizations
+
+- `Gemma3-Python-22k-1B-f16.gguf` (2489.6 MB) - 16-bit float (original precision, largest file)
+- `Gemma3-Python-22k-1B-q3_k_m.gguf` (850.9 MB) - 3-bit quantization (medium quality)
+- `Gemma3-Python-22k-1B-q4_k_m.gguf` (966.7 MB) - 4-bit quantization (medium, recommended for most use cases)
+- `Gemma3-Python-22k-1B-q5_k_m.gguf` (1027.9 MB) - 5-bit quantization (medium, good quality)
+- `Gemma3-Python-22k-1B-q6_k.gguf` (1270.9 MB) - 6-bit quantization (high quality)
+- `Gemma3-Python-22k-1B-q8_0.gguf` (1325.8 MB) - 8-bit quantization (very high quality)
+
+## Usage
+
+### With llama.cpp
+
+```bash
+# Download recommended quantization
+wget https://huggingface.co/theprint/Gemma3-Python-22k-1B-GGUF/resolve/main/Gemma3-Python-22k-1B-q4_k_m.gguf
+
+# Run inference
+./llama.cpp/main -m Gemma3-Python-22k-1B-q4_k_m.gguf \
+  -p "Your prompt here" \
+  -n 256 \
+  --temp 0.7 \
+  --top-p 0.9
+```
+
+### With other GGUF tools
+
+These files are compatible with:
+- [llama.cpp](https://github.com/ggerganov/llama.cpp)
+- [Ollama](https://ollama.ai/) (import as custom model)
+- [KoboldCpp](https://github.com/LostRuins/koboldcpp)
+- [text-generation-webui](https://github.com/oobabooga/text-generation-webui)
+
+## Quantization Info
+
+**Recommended:** `q4_k_m` provides the best balance of size, speed, and quality for most use cases.
+
+**For maximum quality:** Use `q8_0` or `f16`  
+**For maximum speed/smallest size:** Use `q3_k_m` or `q4_k_s`
+
+## License
+
+mit
+
+## Citation
+
+```bibtex
+@misc{gemma3_python_22k_1b_gguf,
+  title={Gemma3-Python-22k-1B GGUF Quantized Models},
+  author={theprint},
+  year={2025},
+  publisher={Hugging Face},
+  url={https://huggingface.co/theprint/Gemma3-Python-22k-1B-GGUF}
+}
+```