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waghelad
/
ds-rag-embedder-v1

Feature Extraction
sentence-transformers
Safetensors
English
bert
sentence-similarity
rag
retrieval
data-science
machine-learning
embeddings
domain-specific
text-embeddings-inference
hybrid-search
Model card Files Files and versions
xet
Community
1

Instructions to use waghelad/ds-rag-embedder-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use waghelad/ds-rag-embedder-v1 with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("waghelad/ds-rag-embedder-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]
  • Notebooks
  • Google Colab
  • Kaggle
New discussion
Resources
  • PR & discussions documentation
  • Code of Conduct
  • Hub documentation

Launch: DS RAG Embedder v1 — domain embeddings for DS/ML documentation RAG

#1 opened 1 day ago by
waghelad
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