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ISOISS
/
jina-embeddings-v3-tei

Feature Extraction
Transformers
PyTorch
ONNX
Safetensors
sentence-transformers
xlm-roberta
sentence-similarity
mteb
custom_code
Eval Results (legacy)
text-embeddings-inference
Model card Files Files and versions
xet
Community
1

Instructions to use ISOISS/jina-embeddings-v3-tei with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use ISOISS/jina-embeddings-v3-tei with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="ISOISS/jina-embeddings-v3-tei", trust_remote_code=True)
    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("ISOISS/jina-embeddings-v3-tei", trust_remote_code=True)
    model = AutoModel.from_pretrained("ISOISS/jina-embeddings-v3-tei", trust_remote_code=True, device_map="auto")
  • sentence-transformers

    How to use ISOISS/jina-embeddings-v3-tei with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("ISOISS/jina-embeddings-v3-tei", trust_remote_code=True)
    
    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]
  • Notebooks
  • Google Colab
  • Kaggle
New discussion
Resources
  • PR & discussions documentation
  • Code of Conduct
  • Hub documentation

Error with Text-Embeddings-Inference Container using JINA-v3 Model

1
#1 opened almost 2 years ago by
ilhamdprastyo
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