Instructions to use Jeevesh8/bert_ft_cola-52 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/bert_ft_cola-52 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/bert_ft_cola-52")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/bert_ft_cola-52") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/bert_ft_cola-52") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 72d6db0af796dfb1f520a95efabe9c4b8e0589f92877905dc7077932b2170aaf
- Size of remote file:
- 438 MB
- SHA256:
- 395d37f44adbbe2a8f634316466ff82ccd04118045e95f26c25c7a534dcb64e7
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.