Instructions to use HiTZ/BERnaT-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HiTZ/BERnaT-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="HiTZ/BERnaT-base")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("HiTZ/BERnaT-base") model = AutoModelForMaskedLM.from_pretrained("HiTZ/BERnaT-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 85c2c02d025e2678832aab06612310e70401d6c5aaed9474e612e4093a3944df
- Size of remote file:
- 498 MB
- SHA256:
- bb9541694937eef2894aced43bb40e0e1f3aefecec70a38c96d31b21e50327da
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