Instructions to use Jeevesh8/std_0pnt2_bert_ft_cola-75 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-75 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-75")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-75") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-75") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5a9a83f2b38adb22cb5f788f652ab49af50d044ce6bf3db61757b9b7508c5fc5
- Size of remote file:
- 438 MB
- SHA256:
- 067ced6daa7249c973e10721fa126e3b95e561d6ba5f8593e7939e8504e8dae4
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