Instructions to use Jeevesh8/std_0pnt2_bert_ft_cola-48 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/std_0pnt2_bert_ft_cola-48 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/std_0pnt2_bert_ft_cola-48")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-48") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-48") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c7c371e0eee32a14489b771f09cfc74d98cc3741b1e332c2c62e1a684abbe005
- Size of remote file:
- 438 MB
- SHA256:
- 9478261b275b0e5c2dbcb1ac27d6222e3537e767a06b78e27de28bc4567cd5df
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