Awesome GitHub RepositoriesQuantized Model Loading

BigDL is a PyTorch acceleration framework and distributed inference engine designed for large language models. It provides a toolkit for running models on Intel hardware, integrating quantization tools and libraries for parameter-efficient fine-tuning. The project distinguishes itself through the use of pipeline parallelism to distribute model workloads across multiple hardware accelerators. It utilizes low-bit integer quantization and speculative decoding to reduce memory footprints and decrease text generation latency. The system covers broad capabilities in model optimization, including w

This framework provides a toolkit for fine-tuning large language models by combining distributed data parallelism with parameter sharding and quantization techniques. It is designed to scale the training of massive neural networks across multiple graphics processors, enabling the execution of models that exceed the memory capacity of individual hardware units. The library distinguishes itself by integrating low-rank adaptation with memory-efficient weight loading and quantization-aware parameter sharding. By initializing model weights directly on the graphics processor and applying granular l