Instructions to use Jeevesh8/init_bert_ft_qqp-59 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/init_bert_ft_qqp-59 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/init_bert_ft_qqp-59")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/init_bert_ft_qqp-59") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/init_bert_ft_qqp-59") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 37fc0ca16214b3e780c28b255ab1c24e3182a52b5a0d7cb63e5f548fa6469219
- Size of remote file:
- 438 MB
- SHA256:
- ce68ee9d1dd8764bf1f0aae350597717d9366253349da7969519b600e99cacb5
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