Instructions to use textattack/roberta-base-rotten_tomatoes with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use textattack/roberta-base-rotten_tomatoes with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="textattack/roberta-base-rotten_tomatoes")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("textattack/roberta-base-rotten_tomatoes") model = AutoModelForMaskedLM.from_pretrained("textattack/roberta-base-rotten_tomatoes") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 023f8ffa830255470905ca29e9f30fa57091bf0bca53c63148fbd94fe2773dc2
- Size of remote file:
- 501 MB
- SHA256:
- 9c8c2d8c906de9251ed8aa7a94bbc2a9ab6416be87c5d326076fcbbadb917503
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