#training speed

LLaMA-Factory streamlines the fine-tuning of large language models with advanced algorithms and scalable resources. It supports various models such as LLaMA, LLaVA, and Mistral. Offering capabilities like full-tuning, freeze-tuning, and different quantization methods, it enhances training speed and GPU memory usage efficiency. The platform facilitates experiment tracking and offers fast inference through an intuitive API and interface, suitable for developers improving text generation projects.

Developed using graph-mode TensorFlow, Tensorpack is designed for high-speed neural network training and utilizes efficient methods and multi-GPU capabilities. Its outstanding data loading capacity through pure Python complements its support for flexible and reproducible research. Tensorpack is particularly suited for extensive model training in advanced fields such as GANs, object detection, and reinforcement learning, with scripts available to replicate key research papers. Although Tensorpack is continually evolving, it offers a robust model zoo and in-depth documentation to enhance training workflows.