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:
- 3177f49280aa4a19fd5f415a61f6977e13aeeb3b0eba3beb1b1508913fb2a460
- Size of remote file:
- 499 MB
- SHA256:
- d1cd31f97dc5d2ee4e85922acc7e7e352644436d57e4ff582d4d8df19192c938
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