Instructions to use Jeevesh8/bert-base-uncased_cola_ft_17 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/bert-base-uncased_cola_ft_17 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/bert-base-uncased_cola_ft_17")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/bert-base-uncased_cola_ft_17") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/bert-base-uncased_cola_ft_17") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dd8a2e4b0b4d7d8fa7f4b980fc8c38be5f47659240027de92eda34fe3650a720
- Size of remote file:
- 438 MB
- SHA256:
- 0be354a17a1f5bda278fb3e0fa9e370e29e392b4b23f54d16160094e05dbc5f4
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