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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2ecd5997769035b29cefd68d95485a668f556b4fff3cc32ca6ae30f3b69447e3
- Size of remote file:
- 623 Bytes
- SHA256:
- c89fa3caadb7ca0b7615cfb0346ae6d13f4e13a14b6a4c349ca7e187eb6fe574
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