Instructions to use lordtt13/COVID-SciBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lordtt13/COVID-SciBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="lordtt13/COVID-SciBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("lordtt13/COVID-SciBERT") model = AutoModelForMaskedLM.from_pretrained("lordtt13/COVID-SciBERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0e45f38c468629473f4b2a28ee6ec86a9cda6708de39e371372dc079e5f00301
- Size of remote file:
- 442 MB
- SHA256:
- 7a6bd3f7b47e874f2940369edeb4da3e42e7239c0ce67be9ec2fd69f2c895157
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