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Collab-uniba
/
github-issues-preprocessed-mpnet-st-e10

Sentence Similarity
sentence-transformers
PyTorch
Transformers
mpnet
feature-extraction
text-embeddings-inference
Model card Files Files and versions
xet
Community
1

Instructions to use Collab-uniba/github-issues-preprocessed-mpnet-st-e10 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use Collab-uniba/github-issues-preprocessed-mpnet-st-e10 with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("Collab-uniba/github-issues-preprocessed-mpnet-st-e10")
    
    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 Collab-uniba/github-issues-preprocessed-mpnet-st-e10 with Transformers:

    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("Collab-uniba/github-issues-preprocessed-mpnet-st-e10")
    model = AutoModel.from_pretrained("Collab-uniba/github-issues-preprocessed-mpnet-st-e10")
  • Notebooks
  • Google Colab
  • Kaggle
github-issues-preprocessed-mpnet-st-e10 / 1_Pooling
190 Bytes
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  • 1 contributor
History: 1 commit
PeppoCola's picture
PeppoCola
Create 1_Pooling/config.json
6f42cdd almost 3 years ago
  • config.json
    190 Bytes
    Create 1_Pooling/config.json almost 3 years ago