Instructions to use Jeevesh8/bs__qqp_ft_only_data_shuff_17 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/bs__qqp_ft_only_data_shuff_17 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/bs__qqp_ft_only_data_shuff_17")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/bs__qqp_ft_only_data_shuff_17") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/bs__qqp_ft_only_data_shuff_17") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c20d93a48f635d190bf1848aad251b2c291ebd44149e7c2168456355133fa59c
- Size of remote file:
- 115 MB
- SHA256:
- ede9331dcb76359f2efaae550cf3de2affb4e456751f0451dde07b85bbdc2ff7
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.