Instructions to use Jeevesh8/init_bert_ft_qqp-35 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/init_bert_ft_qqp-35 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/init_bert_ft_qqp-35")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/init_bert_ft_qqp-35") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/init_bert_ft_qqp-35") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f0768dde7173379f50a184a502275e136f9503a4df9994ece46c95f9544a20f1
- Size of remote file:
- 438 MB
- SHA256:
- 974c6e3c6e3eaca8a884e38da58ee3b9cedaa8c6533cba0db393d155b4f29e6a
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