Instructions to use TiGa-RCE/gemma-4-12B-it-oQ4e with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use TiGa-RCE/gemma-4-12B-it-oQ4e with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download TiGa-RCE/gemma-4-12B-it-oQ4e --local-dir gemma-4-12B-it-oQ4e
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
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Download README.md from TiGa-RCE/gemma-4-12B-it-oQ4e: direct link, hf CLI and curl.
- Browser
- Download file 508 Bytes
-
https://huggingface.co/TiGa-RCE/gemma-4-12B-it-oQ4e/resolve/main/README.md
- Command line
-
hf download hf://TiGa-RCE/gemma-4-12B-it-oQ4e/README.md
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curl -L -o README.md https://huggingface.co/TiGa-RCE/gemma-4-12B-it-oQ4e/resolve/main/README.md
508 Bytes
metadata
library_name: mlx
tags:
- mlx
- oq
- quantized
This quantization was uploaded on 2026-09-10 and replaces a previous version. If you downloaded this model before this date, please re-download for the updated weights.
gemma-4-12B-it-oQ4e
This model was quantized using oQ (oMLX v0.6.4) mixed-precision quantization.
Quantization details
- Model type: gemma4_unified
- Bits: 4
- Group size: 64
- Format: MLX safetensors