Instructions to use textattack/roberta-base-RTE with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use textattack/roberta-base-RTE with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="textattack/roberta-base-RTE")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("textattack/roberta-base-RTE") model = AutoModelForSequenceClassification.from_pretrained("textattack/roberta-base-RTE", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c8ae3ffe66a47c4de3055ce631efdc93406f911b93a49878f7b64a85d7188cd5
- Size of remote file:
- 501 MB
- SHA256:
- bef51bed9dfec061199d55cc717270d8f48c20a6d673f48e7e9bdb1178c24dd9
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