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---
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}
}
```
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