Instructions to use Jeevesh8/init_bert_ft_qqp-92 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/init_bert_ft_qqp-92 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/init_bert_ft_qqp-92")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/init_bert_ft_qqp-92") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/init_bert_ft_qqp-92") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e6c348e672590f99779846319ede242bbe72c539619cde18245b55b10eba9958
- Size of remote file:
- 438 MB
- SHA256:
- 4cdeb862bfb6f3e0bbe448123fb7bee68a0aba565886dc0feb12e8786dac3cdb
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