Instructions to use textattack/facebook-bart-large-SST-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use textattack/facebook-bart-large-SST-2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="textattack/facebook-bart-large-SST-2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("textattack/facebook-bart-large-SST-2") model = AutoModelForSequenceClassification.from_pretrained("textattack/facebook-bart-large-SST-2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d21d5f74f51f376a13e03a9891715302a3cf162ea9076e9ced1db7e9083b6b39
- Size of remote file:
- 1.06 kB
- SHA256:
- 506966a8da704363457e52c31b4d56f45ac8c0d13442a6024c25ebec5432d974
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