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ncoop57
/
codeformer-java

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

Instructions to use ncoop57/codeformer-java with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use ncoop57/codeformer-java with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("ncoop57/codeformer-java")
    
    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
codeformer-java
501 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 8 commits
ncoop57
Update emission duration for more accurate estimate
ca3f7fa over 4 years ago
  • 1_Pooling
    Updating with freshly trained model over 4 years ago
  • .gitattributes
    1.73 kB
    Updating with freshly trained model over 4 years ago
  • README.md
    2.38 kB
    Updating with freshly trained model over 4 years ago
  • config.json
    735 Bytes
    Updating with freshly trained model over 4 years ago
  • config_sentence_transformers.json
    123 Bytes
    Updating with freshly trained model over 4 years ago
  • emissions.csv
    302 Bytes
    Update emission duration for more accurate estimate over 4 years ago
  • merges.txt
    456 kB
    Updating with freshly trained model over 4 years ago
  • modules.json
    349 Bytes
    Updating with freshly trained model over 4 years ago
  • pytorch_model.bin

    Detected Pickle imports (4)

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

    What is a pickle import?

    499 MB
    xet
    Updating with freshly trained model over 4 years ago
  • sentence_bert_config.json
    53 Bytes
    Updating with freshly trained model over 4 years ago
  • special_tokens_map.json
    239 Bytes
    Updating with freshly trained model over 4 years ago
  • tokenizer.json
    1.36 MB
    Updating with freshly trained model over 4 years ago
  • tokenizer_config.json
    1.3 kB
    Updating with freshly trained model over 4 years ago
  • vocab.json
    798 kB
    Updating with freshly trained model over 4 years ago