Instructions to use anhuu/argument_classification_stance_roberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use anhuu/argument_classification_stance_roberta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="anhuu/argument_classification_stance_roberta")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("anhuu/argument_classification_stance_roberta") model = AutoModelForSequenceClassification.from_pretrained("anhuu/argument_classification_stance_roberta") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e087bcf9bd400eec31645645a04a15982e04e972071b0c6d176cea496e25e97e
- Size of remote file:
- 499 MB
- SHA256:
- c5371091109978237d0dd9dc43bc4120ac9072e6b4e79ef667f098aa0599379c
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