Instructions to use Jeevesh8/bt__qqp_ft_only_data_shuff_9 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/bt__qqp_ft_only_data_shuff_9 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/bt__qqp_ft_only_data_shuff_9")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/bt__qqp_ft_only_data_shuff_9") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/bt__qqp_ft_only_data_shuff_9") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e87bd7a6611aaecc093393c3bffa567f330f75f7f1b23ceb0d70435e6e567082
- Size of remote file:
- 17.5 MB
- SHA256:
- 516960ca04d28ed221d14554691240acb899233f1db1273f805ef63907666111
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.