Instructions to use Jeevesh8/init_bert_ft_qqp-88 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/init_bert_ft_qqp-88 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/init_bert_ft_qqp-88")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/init_bert_ft_qqp-88") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/init_bert_ft_qqp-88") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f895af624c86500db1a41e17344dce65bca8e00dc0bb43944b378186e7245c60
- Size of remote file:
- 438 MB
- SHA256:
- 4aa5996f86f4f659fd2775613763c2de57b3f5d6e2b734d06332920f7a8e004f
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