Instructions to use textattack/distilbert-base-uncased-CoLA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use textattack/distilbert-base-uncased-CoLA with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="textattack/distilbert-base-uncased-CoLA")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("textattack/distilbert-base-uncased-CoLA") model = AutoModelForSequenceClassification.from_pretrained("textattack/distilbert-base-uncased-CoLA", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 287e05d6a39671c7375d3a690d3f27ca483339515a59327818cd3aa039f4918b
- Size of remote file:
- 268 MB
- SHA256:
- c750efae9db6d69a58b4ceb27435bf7a20ef81675108b2b076aabb24ad24e33c
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