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amroadel1
/
elc-bert-sentiment-analyzer

Text Classification
Transformers
PyTorch
bert
custom_code
text-embeddings-inference
Model card Files Files and versions
xet
Community
1

Instructions to use amroadel1/elc-bert-sentiment-analyzer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use amroadel1/elc-bert-sentiment-analyzer with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="amroadel1/elc-bert-sentiment-analyzer", trust_remote_code=True)
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("amroadel1/elc-bert-sentiment-analyzer", trust_remote_code=True)
    model = AutoModelForSequenceClassification.from_pretrained("amroadel1/elc-bert-sentiment-analyzer", trust_remote_code=True)
  • Notebooks
  • Google Colab
  • Kaggle
elc-bert-sentiment-analyzer
418 MB
Ctrl+K
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  • 1 contributor
History: 6 commits
amroadel1's picture
amroadel1
Update modeling_ltgbert.py
64b17ca verified about 2 years ago
  • .gitattributes
    54 Bytes
    Upload 6 files about 2 years ago
  • config.json
    1.25 kB
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  • configuration_ltgbert.py
    4.04 kB
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  • modeling_ltgbert.py
    34 kB
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  • pytorch_model.bin
    418 MB
    xet
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  • special_tokens_map.json
    173 Bytes
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  • tokenizer.json
    370 kB
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  • tokenizer_config.json
    234 Bytes
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  • training_args.bin
    3.5 kB
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