Instructions to use Jeevesh8/bert_ft_cola-57 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/bert_ft_cola-57 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/bert_ft_cola-57")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/bert_ft_cola-57") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/bert_ft_cola-57") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4805955e71d1a51a4a2f788ebe781631a4dbe4d98f07108dbbfcf31f88d8bec1
- Size of remote file:
- 438 MB
- SHA256:
- 142a8eef9a690caf1e2c96017eb3a8f4400606523d90922eb85ac79d86b3cfcf
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