Instructions to use Jeevesh8/init_bert_ft_qqp-12 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/init_bert_ft_qqp-12 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/init_bert_ft_qqp-12")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/init_bert_ft_qqp-12") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/init_bert_ft_qqp-12") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 93b5bbb93f491ac5d66d85d5043885540cb49aa8f2367664b771b28c7ae3ce8d
- Size of remote file:
- 438 MB
- SHA256:
- ca3bb1983d3c12c6836f12090bb65968dca0a61214c7877b25ce18660be244f8
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