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hf-internal-testing
/
tiny-random-UMT5ForSequenceClassification

Text Classification
Transformers
PyTorch
t5
Model card Files Files and versions
xet
Community
6

Instructions to use hf-internal-testing/tiny-random-UMT5ForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use hf-internal-testing/tiny-random-UMT5ForSequenceClassification with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="hf-internal-testing/tiny-random-UMT5ForSequenceClassification")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-UMT5ForSequenceClassification")
    model = AutoModelForSequenceClassification.from_pretrained("hf-internal-testing/tiny-random-UMT5ForSequenceClassification")
  • Notebooks
  • Google Colab
  • Kaggle
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Resources
  • PR & discussions documentation
  • Code of Conduct
  • Hub documentation

Adding `safetensors` variant of this model

#6 opened about 2 years ago by
SFconvertbot

Update tiny models for UMT5ForSequenceClassification

#5 opened almost 3 years ago by
hf-transformers-bot

Update tiny models for UMT5ForSequenceClassification

#4 opened almost 3 years ago by
hf-transformers-bot

Update tiny models for UMT5ForSequenceClassification

#3 opened almost 3 years ago by
hf-transformers-bot

Update tiny models for UMT5ForSequenceClassification

#2 opened almost 3 years ago by
hf-transformers-bot

Update tiny models for UMT5ForSequenceClassification

#1 opened almost 3 years ago by
hf-transformers-bot
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