Instructions to use dweb/deberta-base-CoLA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dweb/deberta-base-CoLA with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dweb/deberta-base-CoLA")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("dweb/deberta-base-CoLA") model = AutoModelForSequenceClassification.from_pretrained("dweb/deberta-base-CoLA", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 88e1508dcbf118fbeb133e85ffb9770f86e970c22915778e3aaebc9de2976f75
- Size of remote file:
- 2.86 kB
- SHA256:
- b0e23507d9f874cda3fbf95fec3c35f49895b99c26fa7e1b1483d58a9f50f258
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