license: gemma
library_name: transformers
pipeline_tag: image-text-to-text
base_model: mlabonne/gemma-3-12b-it-qat-abliterated
tags:
- TensorBlock
- GGUF
mlabonne/gemma-3-12b-it-qat-abliterated - GGUF
This repo contains GGUF format model files for mlabonne/gemma-3-12b-it-qat-abliterated.
The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b5753.
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Prompt template
<bos><start_of_turn>user
{system_prompt}
{prompt}<end_of_turn>
<start_of_turn>model
Model file specification
| Filename | Quant type | File Size | Description |
|---|---|---|---|
| gemma-3-12b-it-qat-abliterated-Q2_K.gguf | Q2_K | 4.768 GB | smallest, significant quality loss - not recommended for most purposes |
| gemma-3-12b-it-qat-abliterated-Q3_K_S.gguf | Q3_K_S | 5.458 GB | very small, high quality loss |
| gemma-3-12b-it-qat-abliterated-Q3_K_M.gguf | Q3_K_M | 6.009 GB | very small, high quality loss |
| gemma-3-12b-it-qat-abliterated-Q3_K_L.gguf | Q3_K_L | 6.480 GB | small, substantial quality loss |
| gemma-3-12b-it-qat-abliterated-Q4_0.gguf | Q4_0 | 6.887 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| gemma-3-12b-it-qat-abliterated-Q4_K_S.gguf | Q4_K_S | 6.935 GB | small, greater quality loss |
| gemma-3-12b-it-qat-abliterated-Q4_K_M.gguf | Q4_K_M | 7.301 GB | medium, balanced quality - recommended |
| gemma-3-12b-it-qat-abliterated-Q5_0.gguf | Q5_0 | 8.232 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| gemma-3-12b-it-qat-abliterated-Q5_K_S.gguf | Q5_K_S | 8.232 GB | large, low quality loss - recommended |
| gemma-3-12b-it-qat-abliterated-Q5_K_M.gguf | Q5_K_M | 8.445 GB | large, very low quality loss - recommended |
| gemma-3-12b-it-qat-abliterated-Q6_K.gguf | Q6_K | 9.661 GB | very large, extremely low quality loss |
| gemma-3-12b-it-qat-abliterated-Q8_0.gguf | Q8_0 | 12.510 GB | very large, extremely low quality loss - not recommended |
Downloading instruction
Command line
Firstly, install Huggingface Client
pip install -U "huggingface_hub[cli]"
Then, downoad the individual model file the a local directory
huggingface-cli download tensorblock/mlabonne_gemma-3-12b-it-qat-abliterated-GGUF --include "gemma-3-12b-it-qat-abliterated-Q2_K.gguf" --local-dir MY_LOCAL_DIR
If you wanna download multiple model files with a pattern (e.g., *Q4_K*gguf), you can try:
huggingface-cli download tensorblock/mlabonne_gemma-3-12b-it-qat-abliterated-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'