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Salesforce
/
SFR-Embedding-Mistral

Feature Extraction
sentence-transformers
Safetensors
Transformers
English
mistral
mteb
Eval Results (legacy)
text-embeddings-inference
Model card Files Files and versions
xet
Community
20

Instructions to use Salesforce/SFR-Embedding-Mistral with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use Salesforce/SFR-Embedding-Mistral with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("Salesforce/SFR-Embedding-Mistral")
    
    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]
  • Transformers

    How to use Salesforce/SFR-Embedding-Mistral with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="Salesforce/SFR-Embedding-Mistral")
    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("Salesforce/SFR-Embedding-Mistral")
    model = AutoModel.from_pretrained("Salesforce/SFR-Embedding-Mistral")
  • Notebooks
  • Google Colab
  • Kaggle
SFR-Embedding-Mistral / lora
Ctrl+K
Ctrl+K
  • 4 contributors
History: 1 commit
yeliu918's picture
yeliu918
add model v1.0
224ed93 over 2 years ago
  • adapter_config.json
    668 Bytes
    add model v1.0 over 2 years ago
  • adapter_model.safetensors
    42 MB
    xet
    add model v1.0 over 2 years ago