Instructions to use Mikelium5/DoctorIntentMainClassifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mikelium5/DoctorIntentMainClassifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Mikelium5/DoctorIntentMainClassifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Mikelium5/DoctorIntentMainClassifier") model = AutoModelForSequenceClassification.from_pretrained("Mikelium5/DoctorIntentMainClassifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 43a428bef127cc8c847c1671726d4b5829cef699c137836b2d379bde213c9392
- Size of remote file:
- 499 MB
- SHA256:
- 2753085cfa89e8c2434a7a296e9d275e52f34d91da4ff722ffe79c465f18b762
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