Instructions to use Jeevesh8/bs__qqp_ft_only_data_shuff_16 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_16 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_16")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/bs__qqp_ft_only_data_shuff_16") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/bs__qqp_ft_only_data_shuff_16") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 675d1e9b964508fa559ee656a90d9e3f644993e7e144c30f379158b21a95b774
- Size of remote file:
- 115 MB
- SHA256:
- acbccd2e7cfb75ecb68e5e924bbc0463d3b07c89be3ff1df6aeb1d915e3dba13
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.