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 nativ-community/embeddinggemma-2-bf16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use nativ-community/embeddinggemma-2-bf16 with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download nativ-community/embeddinggemma-2-bf16 --local-dir embeddinggemma-2-bf16
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
File size: 747 Bytes
4a885a0 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 | {
"transformer_task": "feature-extraction",
"modality_config": {
"text": {
"method": "forward",
"method_output_name": "last_hidden_state"
},
"image": {
"method": "forward",
"method_output_name": "last_hidden_state"
},
"audio": {
"method": "forward",
"method_output_name": "last_hidden_state"
},
"video": {
"method": "forward",
"method_output_name": "last_hidden_state"
},
"message": {
"method": "forward",
"method_output_name": "last_hidden_state",
"format": "structured"
}
},
"module_output_name": "token_embeddings"
} |