Instructions to use textattack/xlnet-base-cased-SST-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use textattack/xlnet-base-cased-SST-2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="textattack/xlnet-base-cased-SST-2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("textattack/xlnet-base-cased-SST-2") model = AutoModelForSequenceClassification.from_pretrained("textattack/xlnet-base-cased-SST-2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 352b60a359e064779f406a691298a89e34ecdb1802a8a9047f20a4044b044591
- Size of remote file:
- 469 MB
- SHA256:
- b8502a9f58944e31280d9bd28e29d904d6a9a961f03f6a106b10fc33d5bdc5b7
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