Instructions to use Jeevesh8/bert_ft_cola-84 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/bert_ft_cola-84 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/bert_ft_cola-84")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/bert_ft_cola-84") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/bert_ft_cola-84") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0c1d526583b00bed235b475c3182767855007ff789ded4adc9a6d003aab96420
- Size of remote file:
- 438 MB
- SHA256:
- 77f3d11528ab68b8ce35d932123045becec14ce1476231d685a9b3d965f0bc02
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.