Instructions to use Jeevesh8/bert_ft_cola-66 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/bert_ft_cola-66 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/bert_ft_cola-66")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/bert_ft_cola-66") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/bert_ft_cola-66") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f0622328df1ac48419ea53bc6e5cfc1157baae57c9ea0c23d24feb47612ed3df
- Size of remote file:
- 438 MB
- SHA256:
- fd8daea27a57e532f56040c8e9efce1c33bcda57aaf3ddca3080e038f63c8564
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