Instructions to use ogoshi2000/stance-nystromformer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ogoshi2000/stance-nystromformer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ogoshi2000/stance-nystromformer")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ogoshi2000/stance-nystromformer") model = AutoModelForSequenceClassification.from_pretrained("ogoshi2000/stance-nystromformer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 15b36ae8a6e699faaed5bfd028edf5c49c79fc93d29d47fb6f187c37305a58b2
- Size of remote file:
- 3.63 kB
- SHA256:
- b3161bba896202214abd8449fb048896500bd0ca0d5de801b2a5121718a245c6
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