Instructions to use ModelTC/bart-base-mrpc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ModelTC/bart-base-mrpc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ModelTC/bart-base-mrpc")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ModelTC/bart-base-mrpc") model = AutoModelForSequenceClassification.from_pretrained("ModelTC/bart-base-mrpc") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 15e1f38c13d09a04d51d35904e11718799220235876c63d753e529c66724e2fa
- Size of remote file:
- 2.99 kB
- SHA256:
- 327097767a37332e9264b31e53092e3bc9959d78156badb3437a1cd7a72599a1
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