Instructions to use Jeevesh8/bert_ft_qqp-83 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/bert_ft_qqp-83 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/bert_ft_qqp-83")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/bert_ft_qqp-83") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/bert_ft_qqp-83") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ad181ba1c49e261f5c3f82d9f84806587dff6befe13b6e222eca3b442f24f6ff
- Size of remote file:
- 438 MB
- SHA256:
- e1a31f7f3aaf0f0fd52b35ac333c8b0a230b26c5abbe8f5a558754c93db4911b
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