Instructions to use textattack/distilbert-base-uncased-SST-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use textattack/distilbert-base-uncased-SST-2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="textattack/distilbert-base-uncased-SST-2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("textattack/distilbert-base-uncased-SST-2") model = AutoModelForSequenceClassification.from_pretrained("textattack/distilbert-base-uncased-SST-2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 22367bdd44bddde559a2e30ec39157e885182ae7a93ee650c4445a77fe964d6d
- Size of remote file:
- 1.06 kB
- SHA256:
- 2aabf89648eaf044354ab7b4b4282cbafd43438c96dca800e124c616e5e5f855
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