Instructions to use marcosgg/bert-small-gl-cased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use marcosgg/bert-small-gl-cased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="marcosgg/bert-small-gl-cased")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("marcosgg/bert-small-gl-cased") model = AutoModelForMaskedLM.from_pretrained("marcosgg/bert-small-gl-cased") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2798a46d2edbaf36e0ae52bba4c7e16dc0fdd11a09674fdcebcda70b954fbb78
- Size of remote file:
- 336 MB
- SHA256:
- f9698178b05bf0b0fd27bc088d9ab36ab730bf30d5c713968c047db52c093b2d
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