Instructions to use Jeevesh8/6ep_bert_ft_cola-47 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/6ep_bert_ft_cola-47 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/6ep_bert_ft_cola-47")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/6ep_bert_ft_cola-47") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/6ep_bert_ft_cola-47", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bff5888ad08fff65ba154c7b886852da21b307c0754add2f6e25532b95315f25
- Size of remote file:
- 438 MB
- SHA256:
- a3499964203f63394511d07de00325dc929f138b84c0aa89520390d9b3790324
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