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Lazyhope
/
unixcoder-clone-detection

Feature Extraction
Transformers
PyTorch
roberta
Model card Files Files and versions
xet
Community
1

Instructions to use Lazyhope/unixcoder-clone-detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use Lazyhope/unixcoder-clone-detection with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="Lazyhope/unixcoder-clone-detection")
    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("Lazyhope/unixcoder-clone-detection")
    model = AutoModel.from_pretrained("Lazyhope/unixcoder-clone-detection")
  • Notebooks
  • Google Colab
  • Kaggle
unixcoder-clone-detection
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  • 1 contributor
History: 2 commits
Lazyhope's picture
Lazyhope
Upload unixcode-base-nine model fine-tuned on PoolC 5fold dataset
76b35db about 3 years ago
  • .gitattributes
    1.48 kB
    initial commit about 3 years ago
  • README.md
    21 Bytes
    initial commit about 3 years ago
  • config.json
    743 Bytes
    Upload unixcode-base-nine model fine-tuned on PoolC 5fold dataset about 3 years ago
  • merges.txt
    444 kB
    Upload unixcode-base-nine model fine-tuned on PoolC 5fold dataset about 3 years ago
  • pytorch_model.bin
    504 MB
    xet
    Upload unixcode-base-nine model fine-tuned on PoolC 5fold dataset about 3 years ago
  • special_tokens_map.json
    957 Bytes
    Upload unixcode-base-nine model fine-tuned on PoolC 5fold dataset about 3 years ago
  • tokenizer_config.json
    1.36 kB
    Upload unixcode-base-nine model fine-tuned on PoolC 5fold dataset about 3 years ago
  • vocab.json
    1.04 MB
    Upload unixcode-base-nine model fine-tuned on PoolC 5fold dataset about 3 years ago