Search Packages

catboost

A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.

coremltools

Core ML tools contain supporting tools for Core ML model conversion, editing, and validation.

onnx2tf

A tool for converting ONNX files to LiteRT/TFLite/TensorFlow, PyTorch native code (nn.Module), TorchScript (.pt), state_dict (.pt), Exported Program (.pt2), and Dynamo ONNX. It also supports direct conversion from LiteRT to PyTorch.

netron

Visualizer for neural network, deep learning and machine learning models

catboost-dev

A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.

openvino2tensorflow

This script converts the ONNX/OpenVINO IR model to Tensorflow's saved_model, tflite, h5, tfjs, tftrt(TensorRT), CoreML, EdgeTPU, ONNX and pb. PyTorch (NCHW) -> ONNX (NCHW) -> OpenVINO (NCHW) -> openvino2tensorflow -> Tensorflow/Keras (NHWC/NCHW) -> TFLite (NHWC/NCHW). And the conversion from .pb to saved_model and from saved_model to .pb and from .pb to .tflite and saved_model to .tflite and saved_model to onnx. Support for building environments with Docker. It is possible to directly access the host PC GUI and the camera to verify the operation. NVIDIA GPU (dGPU) support. Intel iHD GPU (iGPU) support.

tflite2tensorflow

Generate saved_model, tfjs, tf-trt, EdgeTPU, CoreML, quantized tflite, ONNX, OpenVINO, Myriad Inference Engine blob and .pb from .tflite. Support for building environments with Docker. It is possible to directly access the host PC GUI and the camera to verify the operation. NVIDIA GPU (dGPU) support. Intel iHD GPU (iGPU) support. Supports inverse quantization of INT8 quantization model.

deepvac

PyTorch Project Specification.

ultralytics-yolov5

No description available

mlbuild

MLBuild enforces inference performance SLAs in CI, automatically blocking slow ML models before they reach production.

yolov5-inference

YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite

mesh-cognition

Python coupling kernel for Mesh Cognition — per-field admission and state blending for CfC neural networks

mmdnn

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.

ml2rt

Machine learning utilities for model conversion, serialization, loading etc

coreml-pytorch-utils

Coreml Utils for torch based models

torch2coreml

Torch7 -> CoreML

runlocal-hub

Python client for benchmarking and validating ML models on real devices via RunLocal API

pipersr

First super-resolution model designed for Apple Neural Engine. 2x upscale, real-time, on-device.

neuron-ml

A tiny and very high level transfer learning library for image classification 📚

catboost-no-sse4

A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.

langchain-mesh-cognition

LangChain integration for Mesh Cognition — give any agent distributed memory across devices

wnetron

Visualizer for neural network, deep learning and machine learning models