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("text-classification", model="textattack/roberta-base-rotten-tomatoes")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("textattack/roberta-base-rotten-tomatoes") model = AutoModelForSequenceClassification.from_pretrained("textattack/roberta-base-rotten-tomatoes") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 705954bb5ae7862407296c46d2481f9cb74d77560af324976194cb3189984808
- Size of remote file:
- 501 MB
- SHA256:
- aa41675b28a38f1418f0713e5e0fcdad9ca40bf1ed58d26036acf9fe87feade5
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