Instructions to use Jeevesh8/bert_ft_qqp-45 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/bert_ft_qqp-45 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/bert_ft_qqp-45")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/bert_ft_qqp-45") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/bert_ft_qqp-45") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4b33217b77b18b454cbc36c971de085a86cebd5f2749fd6c45e9593bc31f5494
- Size of remote file:
- 438 MB
- SHA256:
- 1e6dd061d1adb40e909b96234f325fcc8bd56963da57505832e6359051876ab5
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