Instructions to use Lianglab/PharmBERT-uncased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Lianglab/PharmBERT-uncased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Lianglab/PharmBERT-uncased")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Lianglab/PharmBERT-uncased") model = AutoModelForMaskedLM.from_pretrained("Lianglab/PharmBERT-uncased") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f600a15648ef4036fa79812d86eb2123ea84e876bb4704b80af56b5c1f898d0b
- Size of remote file:
- 438 MB
- SHA256:
- 1a4f82e6b0b69fbc87ee17da8b3453159620361e50242abeee30982240ca0e47
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