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tylermaister
/
flan-t5-small-triggering

Text Classification
Transformers
Safetensors
English
t5
text2text-generation
intent-classification
flan-t5
trigger-detection
Model card Files Files and versions
xet
Community

Instructions to use tylermaister/flan-t5-small-triggering with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use tylermaister/flan-t5-small-triggering with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="tylermaister/flan-t5-small-triggering")
    # pip install -U transformers accelerate
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
    
    tokenizer = AutoTokenizer.from_pretrained("tylermaister/flan-t5-small-triggering")
    model = AutoModelForSeq2SeqLM.from_pretrained("tylermaister/flan-t5-small-triggering", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
flan-t5-small-triggering
311 MB
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  • 1 contributor
History: 4 commits
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tylermaister
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  • .gitattributes
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  • README.md
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  • config.json
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  • generation_config.json
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  • model.safetensors
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  • special_tokens_map.json
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  • spiece.model
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  • tokenizer.json
    2.42 MB
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  • tokenizer_config.json
    20.8 kB
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  • training_args.bin
    6.03 kB
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  • training_config.json
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