Feature Extraction
MLX
Safetensors
multilingual
embedding_gemma2
mlx-vlm
embedding
sentence-similarity
multimodal
image-feature-extraction
audio-feature-extraction
video-feature-extraction
Instructions to use mlx-community/embeddinggemma-2-bf16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use mlx-community/embeddinggemma-2-bf16 with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download mlx-community/embeddinggemma-2-bf16 --local-dir embeddinggemma-2-bf16
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
Download 2_Normalize/config.json from mlx-community/embeddinggemma-2-bf16: direct link, hf CLI and curl.
- Browser
- Download file 97 Bytes
-
https://huggingface.co/mlx-community/embeddinggemma-2-bf16/resolve/main/2_Normalize/config.json
- Command line
-
hf download hf://mlx-community/embeddinggemma-2-bf16/2_Normalize/config.json
-
curl -L -o config.json https://huggingface.co/mlx-community/embeddinggemma-2-bf16/resolve/main/2_Normalize/config.json
97 Bytes
| { | |
| "module_input_name": "sentence_embedding", | |
| "module_output_name": "sentence_embedding" | |
| } |