Instructions to use Jeevesh8/init_bert_ft_qqp-8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/init_bert_ft_qqp-8 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/init_bert_ft_qqp-8")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/init_bert_ft_qqp-8") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/init_bert_ft_qqp-8") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ca5dfbc9c2536943deb818eecdfcb3c0afe96500e494907fcdfc3e5c053513da
- Size of remote file:
- 438 MB
- SHA256:
- 9eaed6c6682d5ad416716476a0f6ab0f9f1683678775b9f23334e5fc9c8a8704
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