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1024m
/
wassa-2023-emo

Text Classification
Transformers
google-tensorflow TensorFlow
English
roberta
nlp
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use 1024m/wassa-2023-emo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use 1024m/wassa-2023-emo with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="1024m/wassa-2023-emo")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("1024m/wassa-2023-emo")
    model = AutoModelForSequenceClassification.from_pretrained("1024m/wassa-2023-emo")
  • Notebooks
  • Google Colab
  • Kaggle
wassa-2023-emo
1.43 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 14 commits
1024m's picture
1024m
Update README.md
4801216 verified almost 2 years ago
  • .gitattributes
    1.52 kB
    initial commit about 2 years ago
  • README.md
    7.19 kB
    Update README.md almost 2 years ago
  • config.json
    1 kB
    Rename config (2).json to config.json about 2 years ago
  • merges.txt
    456 kB
    Upload 6 files about 2 years ago
  • special_tokens_map.json
    280 Bytes
    Upload 6 files about 2 years ago
  • tf_model.h5
    1.42 GB
    xet
    Upload tf_model.h5 about 2 years ago
  • tokenizer.json
    2.11 MB
    Upload 6 files about 2 years ago
  • tokenizer_config.json
    351 Bytes
    Rename tokenizer_config (1).json to tokenizer_config.json about 2 years ago
  • vocab.json
    798 kB
    Upload 6 files about 2 years ago