Instructions to use Jeevesh8/init_bert_ft_qqp-7 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/init_bert_ft_qqp-7 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/init_bert_ft_qqp-7")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/init_bert_ft_qqp-7") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/init_bert_ft_qqp-7") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d9d2761984a53c9f9484a8ae2feeadde266f45f0f93ef3c3832a1fcf24677e07
- Size of remote file:
- 438 MB
- SHA256:
- 4af58818364ff3f3e83f83f3308b0048b11629b3f34fa41278892abd1eaba632
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