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:
- 0906d733ec06b90be3302f0ce337858c9079a32b1aa2afc89da10cc03d08af3c
- Size of remote file:
- 499 MB
- SHA256:
- af38b4537427b2cd50ea743f715ac48078a25caf5f7dc8f7250676d71ab6bfa0
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