Instructions to use Jeevesh8/std_0pnt2_bert_ft_cola-26 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-26 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-26")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-26") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-26") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f5d27888dbb21032ce027563add2deba61ab43ae77dee238528d57745fe6d18b
- Size of remote file:
- 438 MB
- SHA256:
- fc06ab2c7f4e4f5f4b961f0c5e24cfa9a95966467e5ec5408a76c6522a533668
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