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msgfrom96
/
emotion_model_improved

Text Classification
Transformers
Safetensors
xlm-roberta
Generated from Trainer
Model card Files Files and versions
xet
Community

Instructions to use msgfrom96/emotion_model_improved with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use msgfrom96/emotion_model_improved with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="msgfrom96/emotion_model_improved")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("msgfrom96/emotion_model_improved")
    model = AutoModelForSequenceClassification.from_pretrained("msgfrom96/emotion_model_improved", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
emotion_model_improved
4.48 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 2 commits
msgfrom96's picture
msgfrom96
msgfrom96/xlm_emo_multi_improved
3473893 verified over 1 year ago
  • xlm_multi_emo
    msgfrom96/xlm_emo_multi_improved over 1 year ago
  • .gitattributes
    1.52 kB
    initial commit over 1 year ago
  • README.md
    9.67 kB
    msgfrom96/xlm_emo_multi_improved over 1 year ago
  • config.json
    1.22 kB
    msgfrom96/xlm_emo_multi_improved over 1 year ago
  • model.safetensors
    2.24 GB
    xet
    msgfrom96/xlm_emo_multi_improved over 1 year ago
  • thresholds.json
    370 Bytes
    msgfrom96/xlm_emo_multi_improved over 1 year ago
  • training_args.bin
    5.3 kB
    xet
    msgfrom96/xlm_emo_multi_improved over 1 year ago