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:
- 4cca402380abb57355429af63be0389bed4c75a12a279440de3ba51e9bcaf86c
- Size of remote file:
- 3.63 kB
- SHA256:
- 67333a28e4f00c43e9463296a39729f46fe5c9db2cf32d65e5509c6350eceec2
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