Instructions to use FacebookAI/roberta-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FacebookAI/roberta-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="FacebookAI/roberta-base")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("FacebookAI/roberta-base") model = AutoModelForMaskedLM.from_pretrained("FacebookAI/roberta-base", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f443a860c2b4048b040e5379fb733f9fc4710b1fcaa3a19b41a8ae52b5e42b47
- Size of remote file:
- 656 MB
- SHA256:
- 87aab2d871f622ef848e7d9e985534303793b4f6e96ca7aa0dc541261997eb01
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.