Instructions to use Jeevesh8/init_bert_ft_qqp-95 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/init_bert_ft_qqp-95 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/init_bert_ft_qqp-95")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/init_bert_ft_qqp-95") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/init_bert_ft_qqp-95") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 47b83db92bbf07ce28a10b2c0c21b3f1a9d9258fbeb6f9e0bc88eac53cc4be58
- Size of remote file:
- 438 MB
- SHA256:
- e8ab9a1d8277c96cb07d1a5c5995ed9139925e1c940f76d4e2f76b8953d34efa
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