Instructions to use marcosgg/bert-base-gl-cased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use marcosgg/bert-base-gl-cased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="marcosgg/bert-base-gl-cased")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("marcosgg/bert-base-gl-cased") model = AutoModelForMaskedLM.from_pretrained("marcosgg/bert-base-gl-cased") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1c5f61a85b28d639ae84e65dca54ae59e0ead08140c1140ae40801854c80717d
- Size of remote file:
- 714 MB
- SHA256:
- f43cf7999a24cc0d2c98821316fde6a2504ccc008512c92d1beb9ad11c35880d
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