🚀 New Release: Thorki v1.0.0 This release introduces Thorki, a federated learning system that decouples general and personalized knowledge across all model layers to achieve superior accuracy and efficiency. ✨ Key Features Dual-model design: A small model for preserving client-specific personalized knowledge. A large model for collaboratively learning general knowledge via federated training. Lightweight fusion network that adaptively combines outputs from both models during inference. Efficient personalization using a small adaptation set without compromising privacy. 🧪 Experimental Coverage Evaluated with three model architectures on four datasets under varying data heterogeneity. Includes comprehensive ablation studies validating each component of Thorki. 🔧 Implementation Supports CV and NLP tasks with pre-trained ViT and BERT backbones. Incorporates LoRA-based fine-tuning for parameter-efficient training.