Instructions to use Jeevesh8/init_bert_ft_qqp-22 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/init_bert_ft_qqp-22 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/init_bert_ft_qqp-22")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/init_bert_ft_qqp-22") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/init_bert_ft_qqp-22") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0066b007545cf4f375967cd5a1bd4149049ac72c6127a4439f756fcb9ecd6153
- Size of remote file:
- 438 MB
- SHA256:
- 1221a5cf7530545f905e4e0595fbffbe6a7730fcce1a316fdade6b037b000d08
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