Add pipeline_tag and library_name to metadata

README.md

@@ -1,9 +1,11 @@
 ---
-license: llama3.1
-datasets:
-- yahma/alpaca-cleaned
 base_model:
 - meta-llama/Llama-3.1-8B-Instruct
+datasets:
+- yahma/alpaca-cleaned
+library_name: transformers
+license: llama3.1
+pipeline_tag: text-generation
 ---
 
 # DataFilter
@@ -11,9 +13,10 @@ base_model:
 [![arXiv](https://img.shields.io/badge/arXiv-2510.19207-b31b1b.svg)](https://arxiv.org/abs/2510.19207)
 [![HuggingFace](https://img.shields.io/badge/🤗-Model-yellow)](https://huggingface.co/JoyYizhu/DataFilter)
 
-A defense system designed to protect LLM agent systems against prompt injection attacks. DataFilter provides robust protection while maintaining system utility and performance.
+DataFilter is a test-time model-agnostic defense system designed to protect Large Language Model (LLM) agents against prompt injection attacks. As described in the paper [Defending Against Prompt Injection with DataFilter](https://huggingface.co/papers/2510.19207), it removes malicious instructions from data before it reaches the backend LLM, maintaining high utility while reducing attack success rates to near zero.
 
-Codes: https://github.com/yizhu-joy/DataFilter
+- **Paper:** [Defending Against Prompt Injection with DataFilter](https://huggingface.co/papers/2510.19207)
+- **Repository:** [GitHub - yizhu-joy/DataFilter](https://github.com/yizhu-joy/DataFilter)
 
 ## Quick Start
 
@@ -22,29 +25,32 @@ Codes: https://github.com/yizhu-joy/DataFilter
 ```bash
 conda create -n py312vllm python=3.12
 conda activate py312vllm
-pip install vllm pandas 'accelerate>=0.26.0'
+pip install vllm pandas 'accelerate>=0.26.0' deepspeed datasets==2.20.0
 git clone https://github.com/yizhu-joy/DataFilter.git
 cd DataFilter
 ```
 
-### Run DataFilter Inference demo:
+### Run DataFilter Inference Demo
+To test the DataFilter model, run the provided inference script:
 ```bash
 python filter_inference.py
 ```
 
 ## Citation
 
-If you use DataFilter in your research, please cite our paper:
+If you use DataFilter in your research, please cite the following paper:
 
 ```bibtex
-@misc
-{wang2025datafilter,
-title={Defending Against Prompt Injection with DataFilter},
-author={Yizhu Wang and Sizhe Chen and Raghad Alkhudair and Basel Alomair and David Wagner},
-year={2025},
-eprint={2510.19207},
-archivePrefix={arXiv},
-primaryClass={cs.CR},
-url={https://arxiv.org/abs/2510.19207},
+@misc{wang2025datafilter,
+  title={Defending Against Prompt Injection with DataFilter}, 
+  author={Yizhu Wang and Sizhe Chen and Raghad Alkhudair and Basel Alomair and David Wagner},
+  year={2025},
+  eprint={2510.19207},
+  archivePrefix={arXiv},
+  primaryClass={cs.CR},
+  url={https://arxiv.org/abs/2510.19207}, 
 }
-```
+```
+
+## License
+This model is licensed under the Llama 3.1 Community License. Please refer to the LICENSE file for details.