Instructions to use BSC-LT/roberta-base-biomedical-es with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BSC-LT/roberta-base-biomedical-es with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="BSC-LT/roberta-base-biomedical-es")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("BSC-LT/roberta-base-biomedical-es") model = AutoModelForMaskedLM.from_pretrained("BSC-LT/roberta-base-biomedical-es", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ea2314eaaf5f23e1265a570472c7ad9e1e1908cf8127f40407b1383b629aab59
- Size of remote file:
- 504 MB
- SHA256:
- d720b1dddaef37080df8761bea199e3a307cd86cdd261fe3430a674579118f21
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