Instructions to use amoux/roberta-cord19-1M7k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use amoux/roberta-cord19-1M7k with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="amoux/roberta-cord19-1M7k")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("amoux/roberta-cord19-1M7k") model = AutoModelForMaskedLM.from_pretrained("amoux/roberta-cord19-1M7k") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 40aecc46d5755920900852c79e56d53c15d80f9c9462a8273a3baa414bafe365
- Size of remote file:
- 391 MB
- SHA256:
- 25f29026cda919c314d9bfdde3985622ed9eb47f0679584f1fb6b670766a6d0a
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