Instructions to use GleghornLab/cdsBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GleghornLab/cdsBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="GleghornLab/cdsBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("GleghornLab/cdsBERT") model = AutoModelForMaskedLM.from_pretrained("GleghornLab/cdsBERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f45c07e20e79a68573ace1f638ff060cd769ee93b4b57132f966f75ed4e5c8cb
- Size of remote file:
- 1.68 GB
- SHA256:
- caf17eed905ecf073a5f25588fe1cb0b4e345108c99d2095f21eba7347f7d531
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