Instructions to use dessertlab/violent-python-CodeBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dessertlab/violent-python-CodeBERT with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("dessertlab/violent-python-CodeBERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from dessertlab/violent-python-CodeBERT: direct link, hf CLI and curl.
- Browser
- Download file 707 MB
-
https://huggingface.co/dessertlab/violent-python-CodeBERT/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://dessertlab/violent-python-CodeBERT/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/dessertlab/violent-python-CodeBERT/resolve/main/pytorch_model.bin
707 MB
- Xet hash:
- 22d5b041fad209d933b29026fae386b048ab1d748ee31eeb979c2f1ec6a013ea
- Size of remote file:
- 707 MB
- SHA256:
- f66f5d476fc68aed5d315caacd01bcf0d0ffd8eae274514d63f4149d647130a3
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.