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")# pip install -U transformers accelerate # 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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Link to fine-tuning dataset (#1)
- Link to fine-tuning dataset (097e8d751ad2fd3cdee9c9e881b05df56d134390) Co-authored-by: Julien Chaumond <julien-c@users.noreply.huggingface.co>1786810 -
update model
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