Instructions to use StanfordAIMI/covid-radbert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use StanfordAIMI/covid-radbert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="StanfordAIMI/covid-radbert")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("StanfordAIMI/covid-radbert") model = AutoModel.from_pretrained("StanfordAIMI/covid-radbert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e1df7a45c83d1f8efc59e87777028a10e20b408a42fdad4fa6e6bf4f0a790de2
- Size of remote file:
- 433 MB
- SHA256:
- 5e6d57a82e789e4e0ec3bcfb7080d31525d4f07a9def39b357aa3016af252789
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