Instructions to use Jinchen/roberta-base-finetuned-mrpc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jinchen/roberta-base-finetuned-mrpc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jinchen/roberta-base-finetuned-mrpc")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jinchen/roberta-base-finetuned-mrpc") model = AutoModelForSequenceClassification.from_pretrained("Jinchen/roberta-base-finetuned-mrpc") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b69728100dce8b547fa86bffb61ab19a6b1d16bce4437be5443dab5949d92dec
- Size of remote file:
- 2.67 kB
- SHA256:
- 0494736ff516508ec13937bc587f8ac4d92c4a54f7d060cf0b35b244ece857c6
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