--- base_model: unsloth/Llama-3.2-1B library_name: gguf pipeline_tag: text-generation language: en license: apache-2.0 tags: - gguf - quantized - llama.cpp - titan-llama-3.2-1b model_type: llama quantized_by: theprint --- # TiTan-Llama-3.2-1B - GGUF Quantized Quantized GGUF versions of [TiTan-Llama-3.2-1B](https://huggingface.co/theprint/TiTan-Llama-3.2-1B) for use with llama.cpp and other GGUF-compatible inference engines. ## Original Model - **Base model:** [unsloth/Llama-3.2-1B](https://huggingface.co/unsloth/Llama-3.2-1B) - **Fine-tuned model:** [theprint/TiTan-Llama-3.2-1B](https://huggingface.co/theprint/TiTan-Llama-3.2-1B) - **Quantized by:** theprint ## Available Quantizations - `TiTan-Llama-3.2-1B-f16.gguf` (2364.7 MB) - 16-bit float (original precision, largest file) - `TiTan-Llama-3.2-1B-q3_k_m.gguf` (658.8 MB) - 3-bit quantization (medium quality) - `TiTan-Llama-3.2-1B-q4_k_m.gguf` (770.3 MB) - 4-bit quantization (medium, recommended for most use cases) - `TiTan-Llama-3.2-1B-q5_k_m.gguf` (869.3 MB) - 5-bit quantization (medium, good quality) - `TiTan-Llama-3.2-1B-q6_k.gguf` (974.5 MB) - 6-bit quantization (high quality) - `TiTan-Llama-3.2-1B-q8_0.gguf` (1259.9 MB) - 8-bit quantization (very high quality) ## Usage ### With llama.cpp ```bash # Download recommended quantization wget https://huggingface.co/theprint/TiTan-Llama-3.2-1B-GGUF/resolve/main/TiTan-Llama-3.2-1B-q4_k_m.gguf # Run inference ./llama.cpp/main -m TiTan-Llama-3.2-1B-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 apache-2.0 ## Citation ```bibtex @misc{titan_llama_3.2_1b_gguf, title={TiTan-Llama-3.2-1B GGUF Quantized Models}, author={theprint}, year={2025}, publisher={Hugging Face}, url={https://huggingface.co/theprint/TiTan-Llama-3.2-1B-GGUF} } ```