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Enoch2090
/
MAGI

Feature Extraction
sentence-transformers
PyTorch
Transformers
distilbert
text-embeddings-inference
Model card Files Files and versions
xet
Community
1

Instructions to use Enoch2090/MAGI with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use Enoch2090/MAGI with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("Enoch2090/MAGI")
    
    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]
  • Transformers

    How to use Enoch2090/MAGI with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="Enoch2090/MAGI")
    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("Enoch2090/MAGI")
    model = AutoModel.from_pretrained("Enoch2090/MAGI")
  • Notebooks
  • Google Colab
  • Kaggle
MAGI
266 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 6 commits
Enoch2090's picture
Enoch2090
Update README.md
00ab9a3 over 3 years ago
  • 1_Pooling
    init about 4 years ago
  • .gitattributes
    1.22 kB
    initial commit about 4 years ago
  • README.md
    3.7 kB
    Update README.md over 3 years ago
  • config.json
    580 Bytes
    init about 4 years ago
  • config_sentence_transformers.json
    123 Bytes
    init about 4 years ago
  • modules.json
    229 Bytes
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  • pytorch_model.bin

    Detected Pickle imports (3)

    • "collections.OrderedDict",
    • "torch.FloatStorage",
    • "torch._utils._rebuild_tensor_v2"

    What is a pickle import?

    265 MB
    xet
    init about 4 years ago
  • sentence_bert_config.json
    53 Bytes
    init about 4 years ago
  • special_tokens_map.json
    112 Bytes
    init about 4 years ago
  • tokenizer.json
    712 kB
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  • tokenizer_config.json
    415 Bytes
    init about 4 years ago
  • vocab.txt
    232 kB
    init about 4 years ago