Instructions to use Jeevesh8/std_0pnt2_bert_ft_cola-62 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-62 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-62")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-62") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-62") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dc01fce481eb31ada77682f4ff82d8186649fe309a27dab327f746e11565aacb
- Size of remote file:
- 438 MB
- SHA256:
- 7d49f2039b486dc3c7df2fbc24a0e4284dba40d792a4f3aab90d2d50725d9b36
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