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cometadata
/
snowflake-arctic-ror-affiliations

Sentence Similarity
sentence-transformers
Safetensors
English
multilingual
xlm-roberta
embedding
ror
affiliation-matching
contrastive-learning
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use cometadata/snowflake-arctic-ror-affiliations with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use cometadata/snowflake-arctic-ror-affiliations with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("cometadata/snowflake-arctic-ror-affiliations")
    
    sentences = [
        "That is a happy person",
        "That is a happy dog",
        "That is a very happy person",
        "Today is a sunny day"
    ]
    embeddings = model.encode(sentences)
    
    similarities = model.similarity(embeddings, embeddings)
    print(similarities.shape)
    # [4, 4]
  • Notebooks
  • Google Colab
  • Kaggle
snowflake-arctic-ror-affiliations
2.29 GB
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  • 1 contributor
History: 2 commits
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adambuttrick
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  • .gitattributes
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  • README.md
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  • config.json
    700 Bytes
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  • config_sentence_transformers.json
    290 Bytes
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  • model.safetensors
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    xet
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  • modules.json
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  • sentence_bert_config.json
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  • special_tokens_map.json
    964 Bytes
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  • tokenizer.json
    17.1 MB
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  • tokenizer_config.json
    1.37 kB
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