Instructions to use textattack/xlnet-base-cased-QNLI with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use textattack/xlnet-base-cased-QNLI with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="textattack/xlnet-base-cased-QNLI")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("textattack/xlnet-base-cased-QNLI") model = AutoModelForSequenceClassification.from_pretrained("textattack/xlnet-base-cased-QNLI") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7ea0612614b66a643cd76205ef5b36b86d7412c91a4d53065b262010ff4537ae
- Size of remote file:
- 469 MB
- SHA256:
- 9a3bc92091d5dc4f051b58b7e699453906ca90744c98ebeb19d1e415cccb8e4f
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