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Phora68
/
rapha-embed-clinical-v1

Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
Generated from Trainer
dataset_size:132037
loss:MultipleNegativesRankingLoss
Eval Results (legacy)
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use Phora68/rapha-embed-clinical-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use Phora68/rapha-embed-clinical-v1 with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("Phora68/rapha-embed-clinical-v1")
    
    sentences = [
        "back pain. I'm not sure what to make of it.",
        "Observed: back pain — musculoskeletal system",
        "Patient is frustrated with the medical system",
        "OPQRST — Severity: fever rated 7/10 by patient"
    ]
    embeddings = model.encode(sentences)
    
    similarities = model.similarity(embeddings, embeddings)
    print(similarities.shape)
    # [4, 4]
  • Notebooks
  • Google Colab
  • Kaggle
rapha-embed-clinical-v1
934 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 2 commits
Phora68's picture
Phora68
Upload rapha-embed-clinical-v1 (fine-tuned + GGUF)
4927cad verified about 1 month ago
  • 1_Pooling
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  • checkpoint-1545
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  • checkpoint-500
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  • eval
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  • .gitattributes
    1.52 kB
    initial commit about 1 month ago
  • README.md
    20.6 kB
    Upload rapha-embed-clinical-v1 (fine-tuned + GGUF) about 1 month ago
  • config.json
    790 Bytes
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  • config_sentence_transformers.json
    284 Bytes
    Upload rapha-embed-clinical-v1 (fine-tuned + GGUF) about 1 month ago
  • model.safetensors
    133 MB
    xet
    Upload rapha-embed-clinical-v1 (fine-tuned + GGUF) about 1 month ago
  • modules.json
    429 Bytes
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  • sentence_bert_config.json
    241 Bytes
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  • tokenizer.json
    712 kB
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  • tokenizer_config.json
    443 Bytes
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