Instructions to use serdarcaglar/roberta-base-biomedical-es with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use serdarcaglar/roberta-base-biomedical-es with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="serdarcaglar/roberta-base-biomedical-es")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("serdarcaglar/roberta-base-biomedical-es") model = AutoModelForMaskedLM.from_pretrained("serdarcaglar/roberta-base-biomedical-es") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fc00af81199b38c9cc9daad59517e589bb27f521d85a4aec8aa8c29cd57dd5c6
- Size of remote file:
- 4.03 kB
- SHA256:
- 5b771cdfa4e5bb0c414fb37febe4da218726b4bc010cf15f783c553683c3ab67
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