Instructions to use Jeevesh8/init_bert_ft_qqp-56 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/init_bert_ft_qqp-56 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/init_bert_ft_qqp-56")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/init_bert_ft_qqp-56") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/init_bert_ft_qqp-56") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- aad28ecc9c9387af3af03a388f89069bee40b0624cecdfa273545dfc2b75a91b
- Size of remote file:
- 438 MB
- SHA256:
- 0fcd1affbba563c890f0d81947a24ddbe1a8e031f0fe4952233014a342a351d4
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