Improve model card: Add pipeline tag, paper link, abstract, code, and usage

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  1. README.md +53 -2
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  license: mit
 
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  ---
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- # RouteFinder Checkpoints
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- You may find instructions here: https://github.com/ai4co/routefinder
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  license: mit
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+ pipeline_tag: reinforcement-learning
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  ---
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+ # RouteFinder: Towards Foundation Models for Vehicle Routing Problems
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+ This repository hosts the model checkpoints for **RouteFinder**, a comprehensive foundation model framework designed to tackle various Vehicle Routing Problem (VRP) variants, as presented in the paper [RouteFinder: Towards Foundation Models for Vehicle Routing Problems](https://huggingface.co/papers/2406.15007).
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+
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+ ## Abstract
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+ This paper introduces RouteFinder, a comprehensive foundation model framework to tackle different Vehicle Routing Problem (VRP) variants. Our core idea is that a foundation model for VRPs should be able to represent variants by treating each as a subset of a generalized problem equipped with different attributes. We propose a unified VRP environment capable of efficiently handling any combination of these attributes. The RouteFinder model leverages a modern transformer-based encoder and global attribute embeddings to improve task representation. Additionally, we introduce two reinforcement learning techniques to enhance multi-task performance: mixed batch training, which enables training on different variants at once, and multi-variant reward normalization to balance different reward scales. Finally, we propose efficient adapter layers that enable fine-tuning for new variants with unseen attributes. Extensive experiments on 48 VRP variants show RouteFinder outperforms recent state-of-the-art learning methods. Our code is publicly available at this https URL .
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+
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+ ## Code
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+ The official code repository is available on GitHub: [https://github.com/ai4co/routefinder](https://github.com/ai4co/routefinder)
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+
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+ ## Quickstart
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+
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+ ### Installation
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+ We recommend using [uv](https://github.com/astral-sh/uv) (Python package manager) to manage dependencies:
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+
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+ ```bash
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+ uv venv --python 3.12 # create a new virtual environment
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+ source .venv/bin/activate # activate the virtual environment
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+ uv sync --all-extras # for all dependencies
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+ ```
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+ This project is also compatible with `pip install -e .`.
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+
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+ ### Download data and checkpoints
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+ To download the data and checkpoints from HuggingFace automatically, you can use:
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+
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+ ```bash
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+ python scripts/download_hf.py
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+ ```
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+
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+ ### Running
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+ We recommend exploring [this quickstart notebook](https://github.com/ai4co/routefinder/blob/main/examples/1.quickstart.ipynb) to get started with the `RouteFinder` codebase!
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+
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+ The main runner (example here of main baseline) can be called via:
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+
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+ ```bash
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+ python run.py experiment=main/rf/rf-transformer-100
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+ ```
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+ You may change the experiment by using the `experiment=YOUR_EXP`, with the path under [`configs/experiment`](https://github.com/ai4co/routefinder/tree/main/configs/experiment) directory.
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+
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+ ## Citation
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+ If you find RouteFinder valuable for your research or applied projects, please cite our paper:
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+
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+ ```bibtex
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+ @article{
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+ berto2025routefinder,
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+ title={{RouteFinder: Towards Foundation Models for Vehicle Routing Problems}},
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+ author={Federico Berto and Chuanbo Hua and Nayeli Gast Zepeda and Andr{\'e} Hottung and Niels Wouda and Leon Lan and Junyoung Park and Kevin Tierney and Jinkyoo Park},
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+ journal={Transactions on Machine Learning Research},
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+ issn={2835-8856},
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+ year={2025},
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+ url={https://openreview.net/forum?id=QzGLoaOPiY},
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+ }
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+ ```