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Enables privacy-preserving, distributed fine-tuning of Microsoft's Florence-2 vision model using federated learning techniques (FedAvg/FedProx) and LoRA adapters.
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This project is a technical implementation of standard federated learning algorithms applied to a specific vision-language model. With zero stars and forks, it currently serves as a personal experiment or reference implementation rather than a defensible tool or platform. Frontier labs are unlikely to compete in the federated training niche for specific open-source models.
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