Ultralytics YOLOv5 in PyTorch for object detection, instance segmentation, classification, training, and export.
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Open standard for machine learning interoperability
Unified framework for building enterprise RAG pipelines with small, specialized models
- parsing
- retrieval-augmented-generation
- agents
- generative-ai-tools
🏄 Scalable embedding, reasoning, ranking for images and sentences with CLIP
- bert
- sentence-encoding
- deep-learning
- clip-model
YOLOX is a high-performance anchor-free YOLO, exceeding yolov3~v5 with MegEngine, ONNX, TensorRT, ncnn, and OpenVINO supported. Documentation: https://yolox.readthedocs.io/
- yolox
- yolov3
- onnx
- tensorrt
PyTorch implementation of YOLOv3, YOLOv3-SPP, and YOLOv3-tiny for real-time object detection with training, validation, inference, and multi-format export.
MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g. model conversion and visualization. Convert models between Caffe, Keras, MXNet, Tensorflow, CNTK, PyTorch Onnx and CoreML.
- cntk
- visualization
- tensorflow
- model-converter
1M param OCR model - runs on CPU, 15x faster than tesseract, close to 1B+ param models in accuracy
PyTorch to Keras model convertor
- pytorch
- keras-model-convertor
- keras
- tensorflow
Laya typed decisions on Linux x86_64 via ONNX Runtime
Push-to-talk voice dictation for Linux. 100% local, multilingual (25+ languages), with speaker diarization. Qt frontend, Rust backend on NVIDIA Parakeet via ONNX Runtime. KDE Plasmoid integrated.
- asr
- linux
- nvidia
- parakeet