Instructions to use citruschao/bert_edit_intent_classification1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use citruschao/bert_edit_intent_classification1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="citruschao/bert_edit_intent_classification1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("citruschao/bert_edit_intent_classification1") model = AutoModelForSequenceClassification.from_pretrained("citruschao/bert_edit_intent_classification1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a17bfb131f7e602a9c9031e0949dbcbd7a7f79bc8713ad3d0b0a7037a57937fd
- Size of remote file:
- 438 MB
- SHA256:
- 71fad1798e7e6e325e07f0d5bd33796aa6185c0da965c78eb1e74867d5e2942b
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