Instructions to use Jeevesh8/init_bert_ft_qqp-0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/init_bert_ft_qqp-0 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/init_bert_ft_qqp-0")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/init_bert_ft_qqp-0") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/init_bert_ft_qqp-0") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 28947811e159d1fb645af104864f882329560bf130ba2e310e316cdac89ed35f
- Size of remote file:
- 438 MB
- SHA256:
- 6a4cae31dbc0b0b4c48d970dd6058e9aef4454651d9b1dbb7bedef6556f9c3e1
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