Instructions to use textattack/facebook-bart-large-CoLA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use textattack/facebook-bart-large-CoLA with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="textattack/facebook-bart-large-CoLA")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("textattack/facebook-bart-large-CoLA") model = AutoModelForSequenceClassification.from_pretrained("textattack/facebook-bart-large-CoLA", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8af04da6b3eea9d92bac7dfb9df9f46725276ccb6c4c5bd7ec74a1bb704dc270
- Size of remote file:
- 1.63 GB
- SHA256:
- 63d8e4d427e3070a3d4947b647f4386fdb957c2748c274c7e7b320d48c67e487
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