Instructions to use Jeevesh8/std_0pnt2_bert_ft_cola-8 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-8 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-8")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-8") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-8") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 08db37d854f6f280630bec0f778a285ff98c372d8f8db9ae441a269b282d3c97
- Size of remote file:
- 438 MB
- SHA256:
- 54e39d098c2411c08c8bf489bc7bd52d442ae62aa04be1aea16a5d948767e62c
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