Instructions to use Jeevesh8/init_bert_ft_qqp-29 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/init_bert_ft_qqp-29 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/init_bert_ft_qqp-29")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/init_bert_ft_qqp-29") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/init_bert_ft_qqp-29") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 856a6617b01e47e7f53ea228fd11907ea485fb47e209e520bf073262420c6bac
- Size of remote file:
- 438 MB
- SHA256:
- 70139df2aa471133114a92f7af9a6180c401c3bcb52c49ca50a03a5c8652bf7a
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