Instructions to use Jeevesh8/init_bert_ft_qqp-26 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/init_bert_ft_qqp-26 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/init_bert_ft_qqp-26")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/init_bert_ft_qqp-26") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/init_bert_ft_qqp-26") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8eafdd29e41c71ddf0cd58d10de6f88268cb42182a08126f3780de46816c5655
- Size of remote file:
- 438 MB
- SHA256:
- 5dc59ec3a7db6f5110291b65a83e0464d1376dd7cae9b0967a61b0c6497a67ce
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.