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:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Serj/intent-classifier") model = AutoModelForSeq2SeqLM.from_pretrained("Serj/intent-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Adapted model to be more general. Accuracy ~60 on Banking77 and ~80 on Atis.
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Improved model 87 weighted F1 and 86 accuracy (micro average) on Atis
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Add clinc_oos dataset sub samples to training dataset
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initial commit
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