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
| { | |
| "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" | |
| } | |