Instructions to use Jeevesh8/bert_ft_cola-86 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/bert_ft_cola-86 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/bert_ft_cola-86")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/bert_ft_cola-86") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/bert_ft_cola-86") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d2da11192a0718b47b9ebe8e38bc9782de1b670afcc6d72bcd0a6d58c70659fd
- Size of remote file:
- 438 MB
- SHA256:
- 341fd3af9189997f8340bbd567f582409585a7453e8a5d9971e90a5b6cdb154c
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