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batteryswapaichallenge/BatterySwapAI2026-Example
BatterySwapAI2026-Example is a machine learning model from batteryswapaichallenge. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as mit.
This repository shows how to create a solution for the BatterySwapAI 2026 challenge.
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Updated Aug 17, 2026
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From the Hugging Face model README
This repository shows how to create a solution for the BatterySwapAI 2026 challenge.
It contains working example code that can be submitted as-is, along with tools to check the solution before submitting.
You need to have the following installed
On Linux / Mac OS / Windows Subsystem for Linux (WSL)
python -m venv venv
source venv/bin/activate
Install dependencies
pip install -r requirements.txt -r requirements.dev.txt
Run the training
python batteryswap_example/train.py
Trained models or other output used by submission processing (script.py),
must be committed in the git repository.
An example is batteryswap_example/planners/best.pickle.
Using Docker allows to have exactly the same software versions as the submissions system.
This helps to ensure there are no errors when running in the submission environment.
NOTE: this requires around 20 GB+ of disk space.
Build Docker image
docker build -t batteryswapai-2026-example .
Make submissions and run evaluation
docker run --name batteryswapai -v ./dataset:/tmp/data batteryswapai-2026-example bash -c "/app/env/bin/python3 script.py && /app/env/bin/python3 -m batteryswap_public.metric"
Copy submission.csv out of container
docker cp batteryswapai:/app/submission.csv ./submission.csv
NOTE: remember to commit and push your changes to the HuggingFace model repository.
Use New submission in the competition application to submit your current code for evaluation.