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:
- 5fdad4a4253a478072e313320eec293cc525b24c52327ee67aa5623d1d0fa0b3
- Size of remote file:
- 528 MB
- SHA256:
- ba04dc85ea3bbbb275d3c3de1199e2ec42ecab655fe79a3fbe8998bedde3800b
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