Instructions to use deepcode-ai/Prompt-Injection-LLM01 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Adapters
How to use deepcode-ai/Prompt-Injection-LLM01 with Adapters:
from adapters import AutoAdapterModel model = AutoAdapterModel.from_pretrained("undefined") model.load_adapter("deepcode-ai/Prompt-Injection-LLM01", set_active=True) - Notebooks
- Google Colab
- Kaggle
| from setuptools import setup, find_packages | |
| import setuptools | |
| setup( | |
| name="prompt_injection", | |
| version="0.1.0", | |
| description="A brief description of your project", | |
| long_description=open('README.md').read(), | |
| long_description_content_type='text/markdown', | |
| url="", | |
| author="", | |
| author_email="", | |
| license="MIT", | |
| classifiers=[ | |
| "Programming Language :: Python :: 3", | |
| "License :: OSI Approved :: MIT License", | |
| "Operating System :: OS Independent", | |
| ], | |
| packages=find_packages(), | |
| python_requires='>=3.6', | |
| install_requires=[ | |
| # List your project's dependencies here | |
| "requests", | |
| "numpy", | |
| "pandas", | |
| ], | |
| entry_points={ | |
| "console_scripts": [ | |
| "your_command=your_package.module:function", | |
| ], | |
| }, | |
| include_package_data=True, | |
| package_data={ | |
| # Include any data files that need to be bundled with the package | |
| "": ["*.txt", "*.md"], | |
| }, | |
| ) |