metadata
license: apache-2.0
library_name: swarmfl
tags:
- federated-learning
- flower
- multi-agent-systems
- tabular-classification
- research
SwarmFL
Small Flower demo for authorized specialist consultation. Synthetic only; not a benchmark or clinical model.
Quickstart
pip install swarmfl==0.1.0
swarmfl-quickstart --output demo --feedback
python -c "import json; print(json.load(open('demo/result.json')))"
The command starts three local Flower nodes, registers their declarations, performs
a selected one-peer consultation on a new case, and writes the fused probability
and audit artifacts under demo/. The synthetic specialists use the ordered input
views (x0,x1), (x2,x3), and (x4,x5).
The demo keeps specialist views separate, makes one selected peer request, and fuses the observed predictions.
python demo.py --feedback
If needed, install the package first:
pip install swarmfl==0.1.0
The public Hub release contains no research datasets, frozen tests, private checkpoints, or experiment outputs. See the repository for source and research context.