In this study, the particle swarm optimization (PSO) algorithm is applied to address these challenges. The parameters that are optimized include the elements' excitation amplitude, excitation phase, ...

This chapter focuses on methods to enable efficient fine‐tuning of LLMs to downstream tasks through cost optimization. These techniques are collectively referred as parameter‐efficient fine‐tuning, or ...

Code for the paper Initialization using Update Approximation is a Silver Bullet for Extremely Efficient Low-Rank Fine-Tuning LoRA-SB is built on top of HuggingFace Transformers and PEFT libraries, ...

Neural is a domain-specific language (DSL) designed for defining, training, debugging, and deploying neural networks. With declarative syntax, cross-framework support, and built-in execution tracing ...