Fed-Legal is an English-only, five-silo, federated supervised fine-tuning (SFT) dataset for legal language tasks.
It converts selected legal benchmark datasets into a shared chat-style schema suitable for instruction tuning and federated learning experiments.
Each silo corresponds to a different legal task family or dataset source.
The dataset is intentionally non-IID by construction: each client_id represents a different… See the full description on the dataset page: https://huggingface.co/datasets/flwrlabs/fed-legal.
