Instructions to use chkla/roberta-argument with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use chkla/roberta-argument with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="chkla/roberta-argument")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("chkla/roberta-argument") model = AutoModelForSequenceClassification.from_pretrained("chkla/roberta-argument") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2c0874d78a05bffcc8bf4d2b3eb81bcd1ec3b14e030e267f3463365726fb9fe6
- Size of remote file:
- 499 MB
- SHA256:
- 8682b4bf3bd19aa67cae373a19aff476d9a232fadd6d8ee4a5a5facf5f70dcef
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