Instructions to use Databook/SmolClassifierMed with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Databook/SmolClassifierMed with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Databook/SmolClassifierMed")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Databook/SmolClassifierMed") model = AutoModel.from_pretrained("Databook/SmolClassifierMed") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 58a5d45ebcd7519e4fe50bc73543ed084f82d1a454d078aeaa537163bf066bc1
- Size of remote file:
- 1.45 GB
- SHA256:
- 225b655ce5f874c5abb4c38307ed461a3339a3260147a0e4fe0716f73f1c31c1
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