Open standard for machine learning interoperability
Repository Index
47,133 repositories indexed
1–9 of 9 · Most stars
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
An MLOps framework to package, deploy, monitor and manage thousands of production machine learning models
Open-source library of optimized deep learning operations (matmul, convolution, attention) for CPUs (x64, AArch64, RISC-V) and Intel GPUs. Used by PyTorch, TensorFlow, OpenVINO, and ONNX Runtime.
- onednn
- oneapi
- performance
- cpp
How to Copy Text from Images ? Answer is TextSnatcher !. Perform OCR operations in seconds on Linux Desktop.
Kubernetes operator for self-hosted LLM inference across a heterogeneous GPU fleet: NVIDIA CUDA, AMD Vulkan, and Apple Silicon Metal. Runtimes: llama.cpp, vLLM, TGI, mlx-server. Multi-GPU sharding, model caching, OpenAI-compatible endpoints. Apache-2.0, run across homelab and on-prem fleets, actively developed.
This repository provides a set of tools and libraries to integrate Intel® OpenVINO™ Toolkit with ROS 2 (Robot Operating System), enabling efficient deployment of deep learning models for computer vision applications on Intel® hardware.
Accelerated tensor operations and dynamic neural networks based on reverse mode automatic differentiation for every device that can run Swift - from watchOS to Linux
- deep-learning
- deep-neural-networks
- gradient-descent
- automatic-differentiation
Conflict-free merge for DataFrames, JSON, ML models & distributed agents — powered by CRDTs. The first merge library where every operation is mathematically guaranteed to converge.
- collaborative-editing
- conflict-resolution
- crdt
- data-engineering