80 lines
2.3 KiB
Markdown
80 lines
2.3 KiB
Markdown
---
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base_model: google/gemma-3-270m-it
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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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- titan-gemma3-0.27b
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model_type: llama
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quantized_by: theprint
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---
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# TiTan-Gemma3-0.27B - GGUF Quantized
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Quantized GGUF versions of [TiTan-Gemma3-0.27B](https://huggingface.co/theprint/TiTan-Gemma3-0.27B) for use with llama.cpp and other GGUF-compatible inference engines.
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## Original Model
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- **Base model:** [google/gemma-3-270m-it](https://huggingface.co/google/gemma-3-270m-it)
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- **Fine-tuned model:** [theprint/TiTan-Gemma3-0.27B](https://huggingface.co/theprint/TiTan-Gemma3-0.27B)
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- **Quantized by:** theprint
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## Available Quantizations
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- `TiTan-Gemma3-0.27B-f16.gguf` (837.7 MB) - 16-bit float (original precision, largest file)
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- `TiTan-Gemma3-0.27B-q3_k_m.gguf` (320.8 MB) - 3-bit quantization (medium quality)
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- `TiTan-Gemma3-0.27B-q4_k_m.gguf` (351.4 MB) - 4-bit quantization (medium, recommended for most use cases)
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- `TiTan-Gemma3-0.27B-q5_k_m.gguf` (368.0 MB) - 5-bit quantization (medium, good quality)
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- `TiTan-Gemma3-0.27B-q6_k.gguf` (439.9 MB) - 6-bit quantization (high quality)
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- `TiTan-Gemma3-0.27B-q8_0.gguf` (448.0 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/TiTan-Gemma3-0.27B-GGUF/resolve/main/TiTan-Gemma3-0.27B-q4_k_m.gguf
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# Run inference
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./llama.cpp/main -m TiTan-Gemma3-0.27B-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{titan_gemma3_0.27b_gguf,
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title={TiTan-Gemma3-0.27B 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/TiTan-Gemma3-0.27B-GGUF}
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}
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```
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