Instructions to use Aktsvigun/roberta_large_cola with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Aktsvigun/roberta_large_cola with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Aktsvigun/roberta_large_cola")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Aktsvigun/roberta_large_cola") model = AutoModelForSequenceClassification.from_pretrained("Aktsvigun/roberta_large_cola", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 60d039c8596269871e2fd90578ee2a0e56f415dde2212fd58809dc7c6de8e413
- Size of remote file:
- 1.42 GB
- SHA256:
- 7ec76a396260ab56a8b4e12dbc3ab64dc9662aa53e50ac2b703693fa961f26b1
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