Instructions to use mlx-community/embeddinggemma-300m-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use mlx-community/embeddinggemma-300m-4bit with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("mlx-community/embeddinggemma-300m-4bit") sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - MLX
How to use mlx-community/embeddinggemma-300m-4bit with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir embeddinggemma-300m-4bit mlx-community/embeddinggemma-300m-4bit
- Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- LM Studio
| { | |
| "boi_token": "<start_of_image>", | |
| "bos_token": { | |
| "content": "<bos>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false | |
| }, | |
| "eoi_token": "<end_of_image>", | |
| "eos_token": { | |
| "content": "<eos>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false | |
| }, | |
| "image_token": "<image_soft_token>", | |
| "pad_token": { | |
| "content": "<pad>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false | |
| }, | |
| "unk_token": { | |
| "content": "<unk>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false | |
| } | |
| } | |