jcwchen

drone_view_building_identification

Drone-view building identification by cross-view Triplet deep neural network and relative spatial estimation

MLabHack2020

onnx

Open standard for machine learning interoperability

tensorflow_alexnet_classification

Experiment on AlexNet (Krizhevsky, Alex, Ilya Sutskever, and Geoffrey E. Hinton. "Imagenet classification with deep convolutional neural networks." Advances in neural information processing systems. 2012.)

tensorflow_triplet

Triplet with AlexNet

Olive

Olive: Simplify ML Model Finetuning, Conversion, Quantization, and Optimization for CPUs, GPUs and NPUs.

onnxruntime

ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator

onnx

Open standard for machine learning interoperability

pytorch

Tensors and Dynamic neural networks in Python with strong GPU acceleration

onnxruntime_backend

The Triton backend for the ONNX Runtime.

jcwchen/onnx

Open standard for machine learning interoperability

jcwchen/onnx-script

ONNX Script enables developers to naturally author ONNX functions and models using a subset of Python. ⚠️ ONNX Script is in very early and active development and is not ready for production.

jcwchen/onnxmltools

ONNXMLTools enables conversion of models to ONNX

jcwchen/pybind11

Seamless operability between C++11 and Python

jcwchen/sklearn-onnx

Convert scikit-learn models and pipelines to ONNX

jcwchen/app

GitHub App that enforces the Developer Certificate of Origin (DCO) on Pull Requests

jcwchen/backend-scoreboard

Scoreboard for ONNX Backend Compatibility

jcwchen/benchmark

TorchBench is a collection of open source benchmarks used to evaluate PyTorch performance.

jcwchen/gradio

Create UIs for prototyping your machine learning model in 3 minutes

jcwchen/jcwchen

Intro

jcwchen/mlagility

Machine Learning Agility (MLAgility) benchmark and benchmarking tools

jcwchen/models

A collection of pre-trained, state-of-the-art models in the ONNX format

jcwchen/mypy

Optional static typing for Python

jcwchen/numpy

The fundamental package for scientific computing with Python.

jcwchen/onnx-docker

Dockerfiles and scripts for ONNX container images

jcwchen/onnx-feedstock

A conda-smithy repository for onnx.

jcwchen/onnx-mlir

Representation and Reference Lowering of ONNX Models in MLIR Compiler Infrastructure

jcwchen/onnx-tensorflow

Tensorflow Backend for ONNX

jcwchen/onnx.github.io

jcwchen/onnxruntime

ONNX Runtime: cross-platform, high performance scoring engine for ML models

jcwchen/onnxruntime-feedstock

A conda-smithy repository for onnxruntime.

jcwchen/ort

Accelerate PyTorch models with ONNX Runtime

jcwchen/pytorch

Tensors and Dynamic neural networks in Python with strong GPU acceleration

jcwchen/runner

The Runner for GitHub Actions :rocket:

jcwchen/sigs

Repository for ONNX SIG artifacts

jcwchen/spox

Pythonic framework for constructing ONNX graphs.

jcwchen/tensorflow-onnx

Convert TensorFlow models to ONNX

jcwchen/TensorRT

TensorRT is a C++ library for high performance inference on NVIDIA GPUs and deep learning accelerators.

jcwchen/tutorials-1

Tutorials for creating and using ONNX models

jcwchen/TypeScript

TypeScript is a superset of JavaScript that compiles to clean JavaScript output.