Instructions to use Jeevesh8/init_bert_ft_qqp-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/init_bert_ft_qqp-2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/init_bert_ft_qqp-2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/init_bert_ft_qqp-2") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/init_bert_ft_qqp-2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 23e1acb0f6be173c3e66c065b37b747ebc9ca31221f33d6041fec5b511108acf
- Size of remote file:
- 438 MB
- SHA256:
- e05941f46fd04a96d02882782d426dedaf86c1249d0d5261a8c0e7db93f4b733
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