#training data

Discover a groundbreaking method in machine learning that emphasizes efficient data labeling and management to reduce manual labor. Originating from Stanford, this project has joined forces with tech giants like Google and Intel, contributing to over sixty peer-reviewed publications and supporting real-world applications. With Snorkel Flow, the project advances into a comprehensive AI platform, incorporating cutting-edge techniques in weak supervision, data augmentation, and multitask learning, offering researchers and practitioners a streamlined process for AI development.

LLaVA-Plus enhances the functionalities of language and vision assistants by incorporating tool use for vision tasks. It forms multimodal agents capable of learning and utilizing various skills. The project's design simplifies installation and ensures operating system compatibility, offering specific guidance for Linux, macOS, and Windows. Detailed demo setups and training guides enable model deployment and utilization of public checkpoints in the Model Zoo. The training is structured in two stages: feature alignment and tool-enhanced visual instruction tuning, utilizing massive datasets like COCO and VisualGenome. Available for research purposes under defined licenses, the project supports the advancement of multimodal AI by permitting non-commercial use.

Skywork is a series of large open-source models developed by the Tiangong team at Kunlun Wanwei Group, available for commercial applications under specific protocols. Models include Skywork-13B Base, trained on a vast dataset of multilingual and code data, showing top performance in benchmarks. Skywork-13B Chat is designed for enhanced dialogue, perfect for creativity tasks, while Skywork-13B Math excels in mathematical evaluations. Skywork-13B MM supports multimodal data input. The Skypile-150B dataset is the largest open-source Chinese dataset, aiding the study of models and AGI advancements with detailed technical data in the tech report.

Discover the method for creating text-to-video models using GANs in Python. This guide covers key processes such as data coding, pre-processing, and GAN implementation for efficient video generation, suitable for those with limited computing resources.

TeleChat, a semantic large language model developed by China Telecom's AI unit, includes the TeleChat-1B, 7B, and 12B models which are open-source and trained on vast multilingual data. TeleChat-12B features improvements in structure and training that enhance performance in areas like Q&A, coding, and mathematics without exaggeration. The models support advanced deep learning techniques and excel in reasoning, understanding, and long-text generation for a range of uses.