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gabrielloiseau
/
CALE-XLM-R

Sentence Similarity
sentence-transformers
Safetensors
xlm-roberta
feature-extraction
loss:ContrastiveLoss
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use gabrielloiseau/CALE-XLM-R with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use gabrielloiseau/CALE-XLM-R with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("gabrielloiseau/CALE-XLM-R")
    
    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
CALE-XLM-R
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  • 1 contributor
History: 3 commits
gabrielloiseau's picture
gabrielloiseau
Update README.md
ff90d7f verified 9 months ago
  • 1_Pooling
    Add new SentenceTransformer model 9 months ago
  • .gitattributes
    1.57 kB
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  • README.md
    1.65 kB
    Update README.md 9 months ago
  • config.json
    663 Bytes
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  • config_sentence_transformers.json
    283 Bytes
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  • model.safetensors
    2.24 GB
    xet
    Add new SentenceTransformer model 9 months ago
  • modules.json
    229 Bytes
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  • sentence_bert_config.json
    57 Bytes
    Add new SentenceTransformer model 9 months ago
  • special_tokens_map.json
    964 Bytes
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  • tokenizer.json
    17.1 MB
    xet
    Add new SentenceTransformer model 9 months ago
  • tokenizer_config.json
    1.37 kB
    Add new SentenceTransformer model 9 months ago