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THE FIRST COLLECTIONPython library for on-device AI data infrastructure, offering quantized image/text embedding providers, batch indexing for images, videos and documents, incremental clustering, semantic search and few-shot classification.
Magika is Google's AI-powered file content type detection tool. It uses a small deep learning model to identify 200+ file types in milliseconds on a single CPU, with ~99% accuracy. Available as a Rust CLI plus Python, JavaScript and Go bindings.
ONNX Runtime is a cross-platform accelerator for machine learning inference and training, supporting models from PyTorch, TensorFlow, and scikit-learn.
A GPU-resident runtime for TensorRT image-to-image video models, enabling high-performance video upscaling by keeping raw frames on the GPU from decode to encode.
A curated collection of pre-trained, state-of-the-art machine learning models in the ONNX format, spanning computer vision, NLP, generative AI, and graph machine learning. The repository is being deprecated with models migrating to Hugging Face.
YOLOv5 is a fast, accurate computer vision framework in PyTorch for object detection, instance segmentation, and image classification. It supports training on custom datasets, inference from various sources, and exporting models to formats like ONNX, TensorRT, and CoreML.
