Instructions to use ogoshi2000/stance-bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ogoshi2000/stance-bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ogoshi2000/stance-bert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ogoshi2000/stance-bert") model = AutoModelForSequenceClassification.from_pretrained("ogoshi2000/stance-bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 34fa9e032c748da4826f41460401a9f3766433c5408ee8ef1c5e751fb53930ac
- Size of remote file:
- 440 MB
- SHA256:
- f83b9c46c86ba410d5915ee9bf0fb539cc727836e56432c9bf9e0927c4aba246
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