Instructions to use Jeevesh8/std_0pnt2_bert_ft_cola-46 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-46 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-46")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-46") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-46") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b4f4c0524d8906f3efcfd31666406bfdc8ce52c58acfa7c3640b711ca2e620cd
- Size of remote file:
- 438 MB
- SHA256:
- 8d50ef74872b1def0b9ec6b3caccd7998360967527012d2d4a0a1c9028db9098
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