Instructions to use Jeevesh8/init_bert_ft_qqp-84 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/init_bert_ft_qqp-84 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/init_bert_ft_qqp-84")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/init_bert_ft_qqp-84") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/init_bert_ft_qqp-84") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 32dcb28b20c23fd6eee1a8fffcd056d6502870210750ca7b56ddc1d9245dad0a
- Size of remote file:
- 438 MB
- SHA256:
- e31178f15515b2d157454b8c30e3dc920b5aff8bf2498e7021bb95e0161775bc
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