Instructions to use Lazyhope/python-clone-detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Lazyhope/python-clone-detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Lazyhope/python-clone-detection", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Lazyhope/python-clone-detection", trust_remote_code=True) model = AutoModel.from_pretrained("Lazyhope/python-clone-detection", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Lazyhope/python-clone-detection: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/Lazyhope/python-clone-detection/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Lazyhope/python-clone-detection/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Lazyhope/python-clone-detection/resolve/main/pytorch_model.bin
499 MB
- Xet hash:
- da04c1dfb1e2c8db797466789ea9fb4118c6b167b119e022a4aecd19c53d70be
- Size of remote file:
- 499 MB
- SHA256:
- cd61ea43ac55f9dcb691449f3489fbc90638a96a958289b24c7abf6306642f02
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