Instructions to use ModelTC/roberta-base-mrpc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ModelTC/roberta-base-mrpc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ModelTC/roberta-base-mrpc")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ModelTC/roberta-base-mrpc") model = AutoModelForSequenceClassification.from_pretrained("ModelTC/roberta-base-mrpc", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 56c0ef21a007bf798de6efed728ffc0299ce2f2152403aff7f628261e39b7f9c
- Size of remote file:
- 499 MB
- SHA256:
- f80971b6c8251520f777c4dfb9d7688bdb64e130bd9694fbf0ccc5eb7b0768a8
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