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("<base-model-id>") model.load_adapter("deepcode-ai/Prompt-Injection-LLM01", set_active=True) - Notebooks
- Google Colab
- Kaggle
Download requirements.txt from deepcode-ai/Prompt-Injection-LLM01: direct link, hf CLI and curl.
- Browser
- Download file 265 Bytes
-
https://huggingface.co/deepcode-ai/Prompt-Injection-LLM01/resolve/main/requirements.txt
- Command line
-
hf download hf://deepcode-ai/Prompt-Injection-LLM01/requirements.txt
-
curl -L -o requirements.txt https://huggingface.co/deepcode-ai/Prompt-Injection-LLM01/resolve/main/requirements.txt
265 Bytes
| black | |
| flake8 | |
| isort | |
| pip | |
| python-dotenv | |
| -e . | |
| transformers | |
| colab-xterm | |
| langchain | |
| langchain-experimental | |
| googletrans==4.0.0-rc1 | |
| sentence-transformers | |
| kaggle | |
| transformers | |
| umap-learn | |
| plotly | |
| wizmap | |
| gensim | |
| bertopic | |
| spaCy | |
| livelossplot | |
| jailbreakbench | |
| datasets | |
| json_fix | |
| seaborn |