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:
- 91817175f879294a11adfc78004f52178ac2b323232904206e0caf55a66d4ed7
- Size of remote file:
- 499 MB
- SHA256:
- 481e4699a0589ea0af3e2b36671aa677662e830f597f5d1bc60f3cc8bc5cec45
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