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carinnew
/
STdictabert-max

Sentence Similarity
sentence-transformers
Safetensors
Transformers
bert
feature-extraction
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use carinnew/STdictabert-max with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use carinnew/STdictabert-max with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("carinnew/STdictabert-max")
    
    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]
  • Transformers

    How to use carinnew/STdictabert-max with Transformers:

    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("carinnew/STdictabert-max")
    model = AutoModel.from_pretrained("carinnew/STdictabert-max")
  • Notebooks
  • Google Colab
  • Kaggle
STdictabert-max / eval
5.25 kB
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  • 1 contributor
History: 1 commit
carinnew's picture
carinnew
Upload folder using huggingface_hub
6e6e3e8 verified over 2 years ago
  • binary_classification_evaluation_results.csv
    5.25 kB
    Upload folder using huggingface_hub over 2 years ago