Instructions to use Jeevesh8/bert_ft_cola-48 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/bert_ft_cola-48 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/bert_ft_cola-48")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/bert_ft_cola-48") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/bert_ft_cola-48") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2362f28f789fc4c32118ba76f7f56b2b57978d4a264abc1f17b6e810e05fa873
- Size of remote file:
- 438 MB
- SHA256:
- 0ec0886e60538825111b07b4f592bdd93e86f10202df92b735484e25e5992a07
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