Instructions to use Jeevesh8/std_0pnt2_bert_ft_cola-3 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-3 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-3")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-3") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-3") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 13bd041d7b2beaad78d4cefd8967442d7aeb3cd5e6f6425ef018f744a0d94bde
- Size of remote file:
- 438 MB
- SHA256:
- 93cfb3ddfa48695b1c236af17863f6cb3d70046371a774f54f05a216fd2e8f88
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