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] hf download larkooo/gemma-e2b-rlcd --local-dir gemma-e2b-rlcd
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
Download MANIFEST.in from larkooo/gemma-e2b-rlcd: direct link, hf CLI and curl.
- Browser
- Download file 425 Bytes
-
https://huggingface.co/larkooo/gemma-e2b-rlcd/resolve/main/MANIFEST.in
- Command line
-
hf download hf://larkooo/gemma-e2b-rlcd/MANIFEST.in
-
curl -L -o MANIFEST.in https://huggingface.co/larkooo/gemma-e2b-rlcd/resolve/main/MANIFEST.in
425 Bytes
| include LICENSE THIRD_PARTY_NOTICES.md CONTRIBUTING.md requirements-tested.txt model-source.json | |
| recursive-include docs *.md *.txt *.jpg *.mp4 *.json | |
| recursive-include examples *.json *.jsonl *.txt | |
| recursive-include reports *.md *.json | |
| recursive-include scripts *.py | |
| recursive-include tests *.py *.cjs | |
| recursive-include gemma_rlcd/static *.html *.css *.js *.json *.jpg | |
| global-exclude .DS_Store *.py[cod] *.safetensors *.gguf | |