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
Download vocab.json from codeparrot/unixcoder-java-complexity-prediction: direct link, hf CLI and curl.
- Browser
- Download file 835 kB
-
https://huggingface.co/codeparrot/unixcoder-java-complexity-prediction/resolve/main/vocab.json
- Command line
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hf download hf://codeparrot/unixcoder-java-complexity-prediction/vocab.json
-
curl -L -o vocab.json https://huggingface.co/codeparrot/unixcoder-java-complexity-prediction/resolve/main/vocab.json
835 kB
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