Feature Extraction
MLX
Safetensors
multilingual
embedding_gemma2
mlx-vlm
embedding
sentence-similarity
multimodal
image-feature-extraction
audio-feature-extraction
video-feature-extraction
4-bit precision
Instructions to use mlx-community/embeddinggemma-2-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use mlx-community/embeddinggemma-2-4bit with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download mlx-community/embeddinggemma-2-4bit --local-dir embeddinggemma-2-4bit
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
Download tokenizer.json from mlx-community/embeddinggemma-2-4bit: direct link, hf CLI and curl.
- Browser
- Download file 32.2 MB
-
https://huggingface.co/mlx-community/embeddinggemma-2-4bit/resolve/main/tokenizer.json
- Command line
-
hf download hf://mlx-community/embeddinggemma-2-4bit/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/mlx-community/embeddinggemma-2-4bit/resolve/main/tokenizer.json
32.2 MB
- Xet hash:
- ff29dc00bacbe2db29a89eee9cd86b61be7936ed3d1a755ff69d1b259a18a7c7
- Size of remote file:
- 32.2 MB
- SHA256:
- 4d777ef5bdc1aa36227abdfb77c3e49e7b9c892d16e1b6bda41c393504828be4
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