Text Classification
Transformers
PyTorch
JAX
Safetensors
code
English
roberta
text-embeddings-inference
Instructions to use Fsoft-AIC/Codebert-docstring-inconsistency with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Fsoft-AIC/Codebert-docstring-inconsistency with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Fsoft-AIC/Codebert-docstring-inconsistency")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Fsoft-AIC/Codebert-docstring-inconsistency") model = AutoModelForSequenceClassification.from_pretrained("Fsoft-AIC/Codebert-docstring-inconsistency") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b42552028fe0d11e49f90ec59cef3955784c98f8f2217c53843d396306a95c6d
- Size of remote file:
- 499 MB
- SHA256:
- 6977f003dbfaa7fa0532a85f47f065f402d22f4c374ec40c7085ce00f1eb1ed9
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