Any-to-Any
MLX
Safetensors
gemma4
mlx-vlm
rlcd
multimodal
classification
parallel-inference
image-text-to-text
audio
video
4-bit precision
Instructions to use larkooo/gemma-e2b-rlcd with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use larkooo/gemma-e2b-rlcd with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir gemma-e2b-rlcd larkooo/gemma-e2b-rlcd
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
File size: 343 Bytes
53e24ca | 1 2 3 4 5 6 7 8 9 10 | {
"repo": "mlx-community/gemma-4-e2b-it-4bit",
"revision": "238767527555cb75a05732a84dff5d6ba0dd6809",
"upstream_model": "google/gemma-4-E2B-it",
"local_directory_example": "models/gemma-4-e2b-it-4bit",
"weights_distributed": true,
"weights_modified": false,
"distribution": "complete_checkpoint_with_parallel_scoring_runtime"
}
|