Instructions to use Jeevesh8/std_0pnt2_bert_ft_cola-17 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-17 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-17")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-17") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-17") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f97a50372b27cc45649ae3ceedb5bf26ebc0f18480cda0bb476bcf7e227f1546
- Size of remote file:
- 438 MB
- SHA256:
- 65fa367a75404268dd2326e779a625049a9f12385cfc8b7f714c5c814058fb49
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