Instructions to use Jeevesh8/bert_ft_cola-36 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/bert_ft_cola-36 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/bert_ft_cola-36")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/bert_ft_cola-36") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/bert_ft_cola-36") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5982ecad23f8c94e7becfe5e3043bb80401dfc26566d64b3b5301b31bc00660e
- Size of remote file:
- 438 MB
- SHA256:
- 10aad3bcb5af7d476c4802c773bb724558744519739134f23372b1a878552fc2
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.