Instructions to use Jeevesh8/init_bert_ft_qqp-6 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/init_bert_ft_qqp-6 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/init_bert_ft_qqp-6")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/init_bert_ft_qqp-6") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/init_bert_ft_qqp-6") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 61f80f7157c3bf9c0aa3fd9f9b2c82fdebc308f6eff33220d1d49a110f6a4b8b
- Size of remote file:
- 438 MB
- SHA256:
- 750bdcd3837ddbd37285cc93fb2287eccbe1ae4ef391fc5f7dc323f514730ef9
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.