Instructions to use Jeevesh8/std_0pnt2_bert_ft_cola-37 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-37 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-37")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-37") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-37") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fa5e6de172d804d3fab448a0e5fb0d8dffc98d60717e7f8aa2ddd3f5fc08dc6e
- Size of remote file:
- 438 MB
- SHA256:
- ed43c23158f47eda2afa9c5c72bea8872258f6d0f5433e3e335b04a0bb39095d
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