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Supreeth
/
DeBERTa-Twitter-Emotion-Classification

Text Classification
Transformers
PyTorch
Safetensors
deberta
Model card Files Files and versions
xet
Community
1

Instructions to use Supreeth/DeBERTa-Twitter-Emotion-Classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use Supreeth/DeBERTa-Twitter-Emotion-Classification with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="Supreeth/DeBERTa-Twitter-Emotion-Classification")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("Supreeth/DeBERTa-Twitter-Emotion-Classification")
    model = AutoModelForSequenceClassification.from_pretrained("Supreeth/DeBERTa-Twitter-Emotion-Classification")
  • Notebooks
  • Google Colab
  • Kaggle
DeBERTa-Twitter-Emotion-Classification
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  • 2 contributors
History: 26 commits
Supreeth's picture
Supreeth
SFconvertbot's picture
SFconvertbot
Adding `safetensors` variant of this model (#1)
dd18b61 over 2 years ago
  • .gitattributes
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    Adding `safetensors` variant of this model (#1) over 2 years ago
  • README.md
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  • config.json
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  • labeleddf.csv
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  • merges.txt
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  • model.safetensors
    557 MB
    xet
    Adding `safetensors` variant of this model (#1) over 2 years ago
  • pytorch_model.bin

    Detected Pickle imports (4)

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

    What is a pickle import?

    557 MB
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  • special_tokens_map.json
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  • tokenizer.json
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  • tokenizer_config.json
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  • vocab.json
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  • vocab.txt
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