Instructions to use Jeevesh8/init_bert_ft_qqp-41 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/init_bert_ft_qqp-41 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/init_bert_ft_qqp-41")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/init_bert_ft_qqp-41") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/init_bert_ft_qqp-41") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 83f48c3e76ab16ae19fbc9d49ebee6d529d0e862edab35a4af2764c21f9d4e4a
- Size of remote file:
- 438 MB
- SHA256:
- 053b3fa39807b437faa296bbb2a217d8e533d9f5f0e77e565a6911b69ada7e5d
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