Text Classification
Transformers
TensorBoard
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use thiomajid/codebert-java-inconsistency with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use thiomajid/codebert-java-inconsistency with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="thiomajid/codebert-java-inconsistency")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("thiomajid/codebert-java-inconsistency") model = AutoModelForSequenceClassification.from_pretrained("thiomajid/codebert-java-inconsistency") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ae409f75a0d0f0160f48c4137a91f251ad037f800e1d47e935b6db612cd9a2f8
- Size of remote file:
- 499 MB
- SHA256:
- 99400ff0fabecd217edaf6aa75203d6e3edaa026f3e9bc01be636a4c1bd7ea50
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.