Instructions to use ModelTC/roberta-base-rte with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ModelTC/roberta-base-rte with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ModelTC/roberta-base-rte")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ModelTC/roberta-base-rte") model = AutoModelForSequenceClassification.from_pretrained("ModelTC/roberta-base-rte", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b893bc5f3783f417ab330e11a89f5d46aaa7bf0b2dc0ac3453608d478cc1794c
- Size of remote file:
- 997 MB
- SHA256:
- 9e15c1e57b0d22bb0bbcf55345061135bedf378bc4101933c524aaacecdac8e2
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