Instructions to use Jeevesh8/init_bert_ft_qqp-83 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/init_bert_ft_qqp-83 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/init_bert_ft_qqp-83")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/init_bert_ft_qqp-83") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/init_bert_ft_qqp-83") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0e3e6147d69a8880aafe8ab5a3fcfd9bcf76146c5b9f265ef796b43aa9f1ea8a
- Size of remote file:
- 438 MB
- SHA256:
- 5b250d48878ca551530cd9e5b6702e22db5bba926fbf2e69c54320f96c8d902e
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