Instructions to use Jeevesh8/std_0pnt2_bert_ft_cola-60 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-60 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-60")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-60") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-60") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5ec11860b8bb65170a13c2ff4e34eaf5540f2caaaf5533a59d2c9114750c032c
- Size of remote file:
- 438 MB
- SHA256:
- 7cf19fa8a67c9b5af987e03684818b0be16241a430fbb2d98e21318a4c139bff
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