README.md

---
license: mit
datasets:
- magicgh/Ask-before-Plan
language:
- en
base_model:
- meta-llama/Meta-Llama-3-8B-Instruct
- mistralai/Mistral-7B-Instruct-v0.2
---

# CEP Framework 

<a href="https://arxiv.org/abs/2406.12639">Paper</a> •
<a href="https://huggingface.co/datasets/magicgh/Ask-before-Plan">Data</a> •
<a href="https://drive.google.com/file/d/1vMIhs8mpMgk33pFDv2rWg6AJNyD70Sod">Environment</a> •
<a href="https://github.com/magicgh/Ask-before-Plan">Code</a>

This repository contains the checkpoint for the CEP framework in our EMNLP 2024 Paper, *Ask-before-Plan: Proactive Language Agents for Real-World Planning*.   
We release our CEP models, including LLaMA-3-8B and Mistral-7B variants, finetuned on Clarification and Execution subtasks.

## Get Started
1. Download our checkpoints.
```bash
git lfs install
git clone https://huggingface.co/magicgh/CEP
```
2. OpenAI compatible servers.
```bash
python3 -m vllm.entrypoints.openai.api_server
  --served-model-name ${model_name}
  --model ${model}
  --kv-cache-dtype fp8
  --port ${port}
  --enable-lora
  --lora-modules ${lora_models}
  --chat-template ${chat_template}
```
## Citation
If you find our research helpful for your work, please star [this repository](https://github.com/magicgh/Ask-before-Plan) and cite our paper:
```
@article{ask-before-plan,
    author = {Xuan Zhang and Yang Deng and Zifeng Ren and See-Kiong Ng and Tat-Seng Chua},
    journal = {ArXiv preprint},
    title = {Ask-before-Plan: Proactive Language Agents for Real-World Planning},
    url = {https://arxiv.org/abs/2406.12639},
    year = {2024}
}
```