Instructions to use codeparrot/unixcoder-java-complexity-prediction with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use codeparrot/unixcoder-java-complexity-prediction with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="codeparrot/unixcoder-java-complexity-prediction")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("codeparrot/unixcoder-java-complexity-prediction") model = AutoModelForSequenceClassification.from_pretrained("codeparrot/unixcoder-java-complexity-prediction") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bf19e230207ecadcd42eba868f3a328db6db748d86be0f695e6cc7883fa49dd4
- Size of remote file:
- 504 MB
- SHA256:
- 9564c11adecbaeb69c032d526496bab1ce5eddb96282f52347aa405909f029d6
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