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 docs/assets/live-demo.mp4 from larkooo/gemma-e2b-rlcd: direct link, hf CLI and curl.
- Browser
- Download file 1.84 MB
-
https://huggingface.co/larkooo/gemma-e2b-rlcd/resolve/main/docs/assets/live-demo.mp4
- Command line
-
hf download hf://larkooo/gemma-e2b-rlcd/docs/assets/live-demo.mp4
-
curl -L -o live-demo.mp4 https://huggingface.co/larkooo/gemma-e2b-rlcd/resolve/main/docs/assets/live-demo.mp4
1.84 MB
- Xet hash:
- a517f902efe7d19a9927cc2a6add74395570b447c0e011d499f1e6ad96e7676e
- Size of remote file:
- 1.84 MB
- SHA256:
- 803559adc8667d1cbf92070943d005ce8659a2e4e2498a83f84b74ac65d80f8b
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