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sentence-transformers
/
clip-ViT-B-32-multilingual-v1

Sentence Similarity
sentence-transformers
PyTorch
google-tensorflow TensorFlow
ONNX
Safetensors
OpenVINO
multilingual
distilbert
feature-extraction
text-embeddings-inference
Model card Files Files and versions
xet
Community
11

Instructions to use sentence-transformers/clip-ViT-B-32-multilingual-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use sentence-transformers/clip-ViT-B-32-multilingual-v1 with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("sentence-transformers/clip-ViT-B-32-multilingual-v1")
    
    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]
  • Inference
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New discussion
Resources
  • PR & discussions documentation
  • Code of Conduct
  • Hub documentation

no gguf format?

#11 opened 8 months ago by
kalle07

Multilingual model for clip-ViT-L-14

#10 opened about 1 year ago by
davidsitsky

The current pytorch doesn't support Nvidia H100 sm90 driver, can it be updated.

#9 opened over 1 year ago by
djjeffr

Adding ONNX file of this model

#8 opened about 2 years ago by
yashvardhan7

Hugging face API and image embedding

#6 opened about 2 years ago by
kovalensue

Exporting model with optimum, but optimum does not take pooling and dense layers into account.

3
#4 opened over 2 years ago by
canavar

Add Core ML conversion

👍 1
#3 opened almost 3 years ago by
maymli

What is the need of separate initialization for img_model and text_model?

🔥 2
#2 opened over 3 years ago by
gokulkarthik

Update README.md

#1 opened over 3 years ago by
lbourdois
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