Instructions to use Jeevesh8/std_0pnt2_bert_ft_cola-35 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-35 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-35")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-35") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-35") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 497b929a363ca16adb8a3bb07995bfec977ee3b0ab6b116f6ff0481e1d011ff3
- Size of remote file:
- 438 MB
- SHA256:
- 3a3ef145dc1b135699de83e7ad2528ef2473e51c140da6a3239c0b0efaf3fe75
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