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:
- 547106a9cfb031b9852cd3356cb144523afd69e22d67f42d01da9ca745c3710b
- Size of remote file:
- 1.53 kB
- SHA256:
- 9feae6e74e28a4936249aadd77ed8bd62a5db6b8ce4e14acc368be85b025bdd9
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