Instructions to use Jeevesh8/init_bert_ft_qqp-71 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/init_bert_ft_qqp-71 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/init_bert_ft_qqp-71")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/init_bert_ft_qqp-71") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/init_bert_ft_qqp-71") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5f09b04feffc650be1bb2441035bd27b0892575981e89fb1eaad25678120d3c2
- Size of remote file:
- 438 MB
- SHA256:
- a18620217601520ab04ad13303b25be458aa4c0ab35f18d6d10c894117e3d6c3
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