Instructions to use Jeevesh8/std_0pnt2_bert_ft_cola-76 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-76 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-76")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-76") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-76") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e79f1e25708227f8e461b770f99094d747613f2b1296869f92ba6465eb23546e
- Size of remote file:
- 438 MB
- SHA256:
- 9e4793b721653b45bb16fc1c6b52d36ffd40dc1465c783e9e38a7bf7998c118a
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