Instructions to use Jeevesh8/init_bert_ft_qqp-15 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/init_bert_ft_qqp-15 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/init_bert_ft_qqp-15")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/init_bert_ft_qqp-15") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/init_bert_ft_qqp-15") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ed12e45637ccc2c11912541ccd8fc0d9c521241f559e31493c1180c016d70a89
- Size of remote file:
- 438 MB
- SHA256:
- 3630ff4269dbce450803cad28110f4129b7aca865b4365ae9592e60a73802d36
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