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:
- 95f6c8ce73d2f40a07213197fe22c68cf4196351a730ca6482c23b12d0ab791b
- Size of remote file:
- 1.05 kB
- SHA256:
- 2bf23b5240e17a6a4abb6b5f131397a2178b50f6d509a791180adc26138441dd
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