Instructions to use Z3NN001/gemma4-21b-a4b-REAP-it-mlx-Q4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use Z3NN001/gemma4-21b-a4b-REAP-it-mlx-Q4 with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir gemma4-21b-a4b-REAP-it-mlx-Q4 Z3NN001/gemma4-21b-a4b-REAP-it-mlx-Q4
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
Gemma-4-21B-A4B-it-REAP (MLX 4-bit)
This is a high-speed 4-bit (INT4) conversion of 0xSero/gemma-4-21b-a4b-it-REAP optimized for Apple Silicon using the MLX framework.
Model Highlights
- Architecture: Gemma 4 Multimodal with Active Blocks (A4B).
- Optimization: REAP (Reasoning Enhancement and Active Pruning) for enhanced vision-language reasoning.
- Precision:
4-bit(Optimized for inference speed and low memory footprint). - Size: ~12 GB (Recommended for any Apple Silicon Mac with 16GB+ RAM).
Conversion Details
The model was converted locally to ensure bit-perfect compatibility with the MLX ecosystem.
- Hardware: Mac Mini (M4) with 32GB RAM.
- Library:
mlx-vlmusing-q --q-bits 4. - Format: Native MLX safetensors.
Usage
Installation
pip install mlx-vlm
Credits
Original Model: 0xSero/gemma-4-21b-a4b-it-REAP
MLX Conversion: Z3NN001
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Model size
21B params
Tensor type
U32
·
BF16 ·
Hardware compatibility
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4-bit
Model tree for Z3NN001/gemma4-21b-a4b-REAP-it-mlx-Q4
Base model
0xSero/Gemma-4-21B