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:
- 88b46444eedac9bf16c2311a51898696a0bf08558d7ad0701e1eb8cdaee0563a
- Size of remote file:
- 1.63 GB
- SHA256:
- 2866760420c317bbce009c22c0befd49c47501278b26cdeb40482bc288e3c674
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