Instructions to use selsar/cv_three_groups_binary with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use selsar/cv_three_groups_binary with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="selsar/cv_three_groups_binary")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("selsar/cv_three_groups_binary") model = AutoModelForSequenceClassification.from_pretrained("selsar/cv_three_groups_binary") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 00d5bf5afa0bff8c12bfabc022f9300a05f335e84759d5e17d385bfaa5065800
- Size of remote file:
- 16.3 MB
- SHA256:
- fac19ea071eaf45a306b764622c743562e1fd17dfd132b715ce76bb5caee26c8
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