Instructions to use lytang/MiniCheck-RoBERTa-Large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lytang/MiniCheck-RoBERTa-Large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="lytang/MiniCheck-RoBERTa-Large")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("lytang/MiniCheck-RoBERTa-Large") model = AutoModelForSequenceClassification.from_pretrained("lytang/MiniCheck-RoBERTa-Large") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bdf0c6d5c3b9abae4a8f2ce0ed40a74c369e4235929a0f51472665c9fec36f20
- Size of remote file:
- 1.42 GB
- SHA256:
- 67af45a2d5a2706283821049232c7d7c81cea22e81dfdbb7097487a98bc61b53
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