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:
- c7ed57e78f0f058f540b1ceab0dd0836d1ebb56f4a81f52af495a4a8c5cb6098
- Size of remote file:
- 1.06 kB
- SHA256:
- 3f4a00cd86671238eeec0123c37175c1fc44d1e67ab62bb8e4a86ce745d36644
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