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Hidden-States
/
roberta-base-emopillars-contextless

Text Classification
Transformers
Safetensors
English
emoaxis
feature-extraction
multi-label-classification
fine-grained
emotion-classification
custom_code
Eval Results (legacy)
Model card Files Files and versions
xet
Community

Instructions to use Hidden-States/roberta-base-emopillars-contextless with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use Hidden-States/roberta-base-emopillars-contextless with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="Hidden-States/roberta-base-emopillars-contextless", trust_remote_code=True)
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("Hidden-States/roberta-base-emopillars-contextless", trust_remote_code=True, dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
roberta-base-emopillars-contextless
503 MB
Ctrl+K
Ctrl+K
  • 2 contributors
History: 8 commits
Subi003's picture
Subi003
Update README.md
8d9592f verified 4 months ago
  • .gitattributes
    1.52 kB
    initial commit 5 months ago
  • README.md
    7.91 kB
    Update README.md 4 months ago
  • config.json
    783 Bytes
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  • configuration_emoaxis.py
    366 Bytes
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  • merges.txt
    456 kB
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  • model.safetensors
    498 MB
    xet
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  • modeling_emoaxis.py
    1.13 kB
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  • special_tokens_map.json
    280 Bytes
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  • tokenizer.json
    3.56 MB
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  • tokenizer_config.json
    1.25 kB
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  • vocab.json
    798 kB
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