Instructions to use Jeevesh8/std_0pnt2_bert_ft_cola-66 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-66 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-66")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-66") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-66") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 51173be199a3925dba82eec14992e86b10e7b35c5cdb9fe962ca35d936324ee8
- Size of remote file:
- 438 MB
- SHA256:
- e858ec73ef77c4a4e47a0e2528101b4a2ce1c27f3b22c782c43a44813a777880
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