Instructions to use jakelever/coronabert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jakelever/coronabert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="jakelever/coronabert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("jakelever/coronabert") model = AutoModelForSequenceClassification.from_pretrained("jakelever/coronabert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
More examples for widget
Browse files
README.md
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license: mit
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- text: "Pre-existing T-cell immunity to SARS-CoV-2 in unexposed healthy controls in Ecuador, as detected with a COVID-19 Interferon-Gamma Release Assay."
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# CoronaCentral BERT Model for Topic / Article Type Classification
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license: mit
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- text: "Pre-existing T-cell immunity to SARS-CoV-2 in unexposed healthy controls in Ecuador, as detected with a COVID-19 Interferon-Gamma Release Assay."
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- text: "Lifestyle and mental health disruptions during COVID-19."
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# CoronaCentral BERT Model for Topic / Article Type Classification
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