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 pytorch_model.bin 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/f8911447f0c571a12bf68b21242f5db16bb39ccc/pytorch_model.bin
- Command line
-
hf download hf://codeparrot/unixcoder-java-complexity-prediction@f8911447f0c571a12bf68b21242f5db16bb39ccc/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/codeparrot/unixcoder-java-complexity-prediction/resolve/f8911447f0c571a12bf68b21242f5db16bb39ccc/pytorch_model.bin
504 MB
- Xet hash:
- 599a1b293e8b1fceca20f6462edbf787a994bab9057f7f911c4ffd33d732689c
- Size of remote file:
- 504 MB
- SHA256:
- 792d49d5a33b67c1dbf4d7f9dbd37e4663ae13032fc8e80fd230cdeea129502b
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