Instructions to use ModelTC/bart-base-rte with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ModelTC/bart-base-rte with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ModelTC/bart-base-rte")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ModelTC/bart-base-rte") model = AutoModelForSequenceClassification.from_pretrained("ModelTC/bart-base-rte", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 54544fae1890e1d663452948813a76552f66ccd9fcea6fec39b3e5b4de313033
- Size of remote file:
- 560 MB
- SHA256:
- 58d7ca032c427618f35d967258eeb531dfc8d79b06c91b7025078166a4129131
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