Instructions to use korca/textfooler-roberta-base-mrpc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use korca/textfooler-roberta-base-mrpc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="korca/textfooler-roberta-base-mrpc")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("korca/textfooler-roberta-base-mrpc") model = AutoModelForSequenceClassification.from_pretrained("korca/textfooler-roberta-base-mrpc") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c1cef29c0d9039614eec5ea92073e19e5d6e2dd53fdff7c22665a0d27cb82ce3
- Size of remote file:
- 499 MB
- SHA256:
- 92dfadb69bcbbfb7dff68d03178be472a43baf91c340fed945dd3c651c221ce9
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