Open-source deep-learning framework for building, training and deploying neural networks on GPUs and CPUs.
KTransformers is a flexible framework for experiencing cutting-edge optimizations in LLM inference and fine-tuning, focusing on CPU-GPU heterogeneous computing. It consists of two core modules: kt-kernel for high-performance inference kernels and kt-sft for fine-tuning. The project supports various hardware and models like DeepSeek series, Kimi-K2, achieving significant resource savings and speedups, such as reducing GPU memory for a 671B model to 70GB and up to 28x acceleration.
A free, open-source Python library that offers a unified API for classical machine-learning algorithms, data-pre-processing, model selection and evaluation.
