Instructions to use Hackxm/Backdoored_Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Hackxm/Backdoored_Model with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Hackxm/Backdoored_Model", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1b4b6d42bfe0d8267e97d26e944458148dd4dae098ee355b747d2a0e94e5f6f7
- Size of remote file:
- 223 MB
- SHA256:
- 0a297b90fb67bb5d5692fd91e6a0618e160650cee158c3569ca99e6ac5db70e3
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