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:
- 0d6faf1af3e40dcfc4db66821612d2f097564e64b137e4fe610491942778f72f
- Size of remote file:
- 664 MB
- SHA256:
- 85b82436a25277f3dc7eb88392607da39c15eaa6987bd129790e698af17c38d5
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