#model zoo

UER-py is a toolkit for pre-training and fine-tuning NLP models on general-domain corpora and downstream tasks. It features a modular architecture supporting models such as BERT and GPT-2, facilitating the extension and utilization of pre-trained models from its model zoo. Achieving high performance in tasks like classification and reading comprehension, UER-py is compatible with CPU and multi-GPU systems, offering comprehensive functions for researchers to explore and optimize advanced models.

TencentPretrain is a comprehensive AI toolkit for pre-training and fine-tuning in text, vision, and audio modalities. Its modular architecture allows for flexible model configuration and scalability. With a diverse model zoo, it offers a range of pre-trained models suited for various tasks. Supporting CPU, single GPU, and distributed training, including DeepSpeed, it ensures superior performance in AI research and applications such as classification and reading comprehension.

Explore a curated selection of models optimized for OpenCV DNN, featuring detailed performance benchmarks on platforms like x86-64, ARM, and RISC-V. This guide provides hardware setup insights for devices from Intel, NVIDIA, and ARM, detailing inference times and showcasing usage examples from face detection to QR code parsing. Ideal for those interested in machine learning, these models offer accessible high-performance solutions for image processing and recognition, ensuring compatibility and efficient application.

Discover a variety of Core ML models ready for integration into iOS apps. This collection includes models for image classification, object detection, and more, all available for download from Google Drive. These models can be implemented in Xcode projects to incorporate advanced machine learning features. Each model is associated with its original project and license for proper legal use, offering developers efficient resources for innovative app development.