Instructions to use ramonzaca/roberto with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ramonzaca/roberto with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="ramonzaca/roberto")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("ramonzaca/roberto") model = AutoModelForMaskedLM.from_pretrained("ramonzaca/roberto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d10ef3089bdc453ef7c4f412f425f0e85264b415047b1a9d8652719927e88930
- Size of remote file:
- 504 MB
- SHA256:
- 9ad7ccd70a51e0709ebb93df5c4875ab033cf1310e7ba19eb4531fb7e8b60abe
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