Instructions to use Jeevesh8/bert_ft_cola-54 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/bert_ft_cola-54 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/bert_ft_cola-54")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/bert_ft_cola-54") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/bert_ft_cola-54") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6a18e618d96db94b9e3825991f43d21db41813e48e758f5daf1c17db8292eabb
- Size of remote file:
- 438 MB
- SHA256:
- 9c93f72cf8100e2c2c276182aeb88f4c8c92de1cded2febd16ed4cf7d40b2a25
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.