Instructions to use ModelTC/bart-base-qnli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ModelTC/bart-base-qnli with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ModelTC/bart-base-qnli")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ModelTC/bart-base-qnli") model = AutoModelForSequenceClassification.from_pretrained("ModelTC/bart-base-qnli", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 50fef9247019132d20070470ad9bc3a3b4b3f56439592d9687cd1d97bdad8826
- Size of remote file:
- 2.99 kB
- SHA256:
- eb099309cc21fb78772567bef42fa8cc80608e82318b04a366d61b3c19e5cdbd
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