Instructions to use stanford-nlpxed/confusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use stanford-nlpxed/confusion with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="stanford-nlpxed/confusion")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("stanford-nlpxed/confusion") model = AutoModelForSequenceClassification.from_pretrained("stanford-nlpxed/confusion") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 86f3d0ddddbc06a0ab6e6e59028f96ce8c1e95e969a999a7e29eb4c7e7620b21
- Size of remote file:
- 4.09 kB
- SHA256:
- 20f5ea9d7b595238fb7cdf087dbd8aa604c18d1bbed67bc97845b60fe1a76a7e
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