Instructions to use Jeevesh8/std_0pnt2_bert_ft_cola-73 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-73 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-73")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-73") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-73") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9acfe848cb94aeee941eeef2706c5c6ef0af64923b7e17107895ed22c12c9f49
- Size of remote file:
- 438 MB
- SHA256:
- 8c6634c007cde768c8197dcebf38730200763a7178176eb5b2c8d3f8ff0f4806
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