Instructions to use textattack/bert-base-uncased-CoLA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use textattack/bert-base-uncased-CoLA with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="textattack/bert-base-uncased-CoLA")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("textattack/bert-base-uncased-CoLA") model = AutoModelForSequenceClassification.from_pretrained("textattack/bert-base-uncased-CoLA") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ed8c427679282b77d954f1941eb2c18081d2f0bf79ddf030a68a6341280bb718
- Size of remote file:
- 438 MB
- SHA256:
- daf55ee85f1607a78c851d0e7ff6fc444b421b436cface3bf521478c22d0beb8
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