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Serj
/
intent-classifier

Transformers
Safetensors
t5
text2text-generation
intent, topic-discovery
text-generation-inference
Model card Files Files and versions
xet
Community

Instructions to use Serj/intent-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use Serj/intent-classifier with Transformers:

    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
    
    tokenizer = AutoTokenizer.from_pretrained("Serj/intent-classifier")
    model = AutoModelForSeq2SeqLM.from_pretrained("Serj/intent-classifier")
  • Notebooks
  • Google Colab
  • Kaggle
intent-classifier
994 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 23 commits
Serj's picture
Serj
Adapted model to be more general. Accuracy ~60 on Banking77 and ~80 on Atis.
532933c verified over 1 year ago
  • .gitattributes
    1.52 kB
    initial commit about 2 years ago
  • README.md
    5.14 kB
    Adapted model to be more general. Accuracy ~60 on Banking77 and ~80 on Atis. over 1 year ago
  • config.json
    1.68 kB
    Adapted model to be more general. Accuracy ~60 on Banking77 and ~80 on Atis. over 1 year ago
  • generation_config.json
    142 Bytes
    Upload T5ForConditionalGeneration about 2 years ago
  • model.safetensors
    990 MB
    xet
    Adapted model to be more general. Accuracy ~60 on Banking77 and ~80 on Atis. over 1 year ago
  • special_tokens_map.json
    2.54 kB
    Upload 3 files about 2 years ago
  • spiece.model
    792 kB
    xet
    Upload spiece.model about 2 years ago
  • tokenizer.json
    2.42 MB
    Upload 3 files about 2 years ago
  • tokenizer_config.json
    20.8 kB
    Upload 3 files about 2 years ago