Fill-Mask
Transformers
PyTorch
Safetensors
English
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roberta
biomedical
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multilingual
Instructions to use HiTZ/EriBERTa-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HiTZ/EriBERTa-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="HiTZ/EriBERTa-base")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("HiTZ/EriBERTa-base") model = AutoModelForMaskedLM.from_pretrained("HiTZ/EriBERTa-base") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 262093f247fc5f76aa9d2d9f30a2f7eb001feb973fa7dd5bb4ad5f843aa23424
- Size of remote file:
- 541 MB
- SHA256:
- dd131e0c2f50bd62d655308807047ec71a6f373ee1686f54ad371e8695f485a4
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