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 model.safetensors from codeparrot/unixcoder-java-complexity-prediction: direct link, hf CLI and curl.
- Browser
- Download file 504 MB
-
https://huggingface.co/codeparrot/unixcoder-java-complexity-prediction/resolve/refs%2Fpr%2F2/model.safetensors
- Command line
-
hf download hf://codeparrot/unixcoder-java-complexity-prediction@refs/pr/2/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/codeparrot/unixcoder-java-complexity-prediction/resolve/refs%2Fpr%2F2/model.safetensors
504 MB
- Xet hash:
- f303e5ff16af2e8c8a953f6485ae42e77a1d309623d563308349abff5ac3c399
- Size of remote file:
- 504 MB
- SHA256:
- 1719622f78746d0fd5eb07d2ba4fbe39a72be55920d39904a712c9fd470b81a0
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