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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- afa85025f55267ff151c85ccd39810f532a561604250224bf89fc9dc240ddeb5
- Size of remote file:
- 664 MB
- SHA256:
- 0d46bb7e8617ce1b87d0f3f79fed155fe7544e29fc7f461da5c4b4b6277f335e
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