Feature Extraction
sentence-transformers
Safetensors
MLX
xlm-roberta
mteb
Sentence Transformers
sentence-similarity
Eval Results (legacy)
text-embeddings-inference
Instructions to use mlx-community/multilingual-e5-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use mlx-community/multilingual-e5-large with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("mlx-community/multilingual-e5-large") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - MLX
How to use mlx-community/multilingual-e5-large with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir multilingual-e5-large mlx-community/multilingual-e5-large
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
| { | |
| "bos_token_id": 151643, | |
| "do_sample": true, | |
| "eos_token_id": [ | |
| 151645, | |
| 151643 | |
| ], | |
| "pad_token_id": 151643, | |
| "repetition_penalty": 1.1, | |
| "temperature": 0.7, | |
| "top_k": 20, | |
| "top_p": 0.8, | |
| "transformers_version": "4.49.0" | |
| } | |