Instructions to use Jeevesh8/bert_ft_cola-29 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/bert_ft_cola-29 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/bert_ft_cola-29")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/bert_ft_cola-29") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/bert_ft_cola-29") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9c926896ae0b7aeba5b1865d353400283d41ffbb8e10cf5b66d9ba713998fd06
- Size of remote file:
- 438 MB
- SHA256:
- 37ddc1dcb7dbcf64cb0b058765a120b023454923d8ec24c5264a9f37826ee71c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.