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io-ts - TypeScript compatible runtime type system for IO decoding/encoding
A value of type Type<A, O, I> (called "runtime type") is the runtime representation of the static type A. Note. The Either type is defined in fp-ts, a library containing implementations of common algebraic types in TypeScript.
typescript validation inference types runtimencnn - ncnn is a high-performance neural network inference framework optimized for the mobile platform
ncnn is a high-performance neural network inference computing framework optimized for mobile platforms. ncnn is deeply considerate about deployment and uses on mobile phones from the beginning of design. ncnn does not have third party dependencies. it is cross-platform, and runs faster than all known open source frameworks on mobile phone cpu. Developers can easily deploy deep learning algorithm models to the mobile platform by using efficient ncnn implementation, create intelligent APPs, and bring the artificial intelligence to your fingertips. ncnn is currently being used in many Tencent applications, such as QQ, Qzone, WeChat, Pitu and so on.
nerual-network inference high-preformance simd arm-neon deep-learning artificial-intelligence android iosNNPACK - Acceleration package for neural networks on multi-core CPUs
NNPACK is an acceleration package for neural network computations. NNPACK aims to provide high-performance implementations of convnet layers for multi-core CPUs. NNPACK is not intended to be directly used by machine learning researchers; instead it provides low-level performance primitives leveraged in leading deep learning frameworks, such as PyTorch, Caffe2, MXNet, tiny-dnn, Caffe, Torch, and Darknet.
neural-network neural-networks convolutional-layers inference high-performance high-performance-computing simd cpu multithreading fast-fourier-transform winograd-transform matrix-multiplicationgrakn - The Knowledge Graph
The Knowledge Graph
grakn graql knowledge-base knowledge-graph knowledge-representation reasoning relational-databases hyper-relational database graph graph-database graph-visualization logic deductions knowledge-engineering enterprise-knowledge-graph knowledge-engine query-language hyper-relational-database inferencejetson-inference - Guide to deploying deep-learning inference networks and deep vision primitives with TensorRT and NVIDIA Jetson
Welcome to our training guide for inference and deep vision runtime library for NVIDIA DIGITS and Jetson Xavier/TX1/TX2. This repo uses NVIDIA TensorRT for efficiently deploying neural networks onto the embedded platform, improving performance and power efficiency using graph optimizations, kernel fusion, and half-precision FP16 on the Jetson.
deep-learning inference computer-vision embedded image-recognition object-detection segmentation jetson jetson-tx1 jetson-tx2delta - DELTA is a deep learning based natural language and speech processing platform.
DELTA is a deep learning based end-to-end natural language and speech processing platform. DELTA aims to provide easy and fast experiences for using, deploying, and developing natural language processing and speech models for both academia and industry use cases. DELTA is mainly implemented using TensorFlow and Python 3. For details of DELTA, please refer to this paper.
nlp deep-learning tensorflow speech sequence-to-sequence seq2seq speech-recognition text-classification speaker-verification nlu text-generation emotion-recognition tensorflow-serving tensorflow-lite inference asr serving front-endtf_trt_models - TensorFlow models accelerated with NVIDIA TensorRT
This repository contains scripts and documentation to use TensorFlow image classification and object detection models on NVIDIA Jetson. The models are sourced from the TensorFlow models repository and optimized using TensorRT. Flash your Jetson TX2 with JetPack 3.2 (including TensorRT).
neural-network tensorflow models realtime inference optimize nvidia image-classification object-detection train tx1 jetson tensorrt tx2torch2trt - An easy to use PyTorch to TensorRT converter
What models are you using, or hoping to use, with TensorRT? Feel free to join the discussion here. Please note, this converter has limited coverage of TensorRT / PyTorch. We created it primarily to easily optimize the models used in the JetBot project. If you find the converter helpful with other models, please let us know.
inference pytorch classification tensorrt jetson-tx2 jetson-xavier jetson-nanoAwesome-System-for-Machine-Learning - A curated list of research in machine learning system
A curated list of research in machine learning system. Link to the code if available is also present. Now we have a team to maintain this project. You are very welcome to pull request by using our template.
infrastructure distributed-systems machine-learning deep-neural-networks system deep-learning optimization paper deep-reinforcement-learning inference automl computer-system edge-computing model-database resouce-managementneuropod - A uniform interface to run deep learning models from multiple frameworks
Neuropod is a library that provides a uniform interface to run deep learning models from multiple frameworks in C++ and Python. Neuropod makes it easy for researchers to build models in a framework of their choosing while also simplifying productionization of these models. It currently supports TensorFlow, PyTorch, TorchScript, Keras and Ludwig.
machine-learning deep-learning tensorflow keras inference pytorch machinelearning deeplearning incubationmulti-model-server - Multi Model Server is a tool for serving neural net models for inference
Multi Model Server (MMS) is a flexible and easy to use tool for serving deep learning models trained using any ML/DL framework. Use the MMS Server CLI, or the pre-configured Docker images, to start a service that sets up HTTP endpoints to handle model inference requests.
ai deep-learning server neural-network mxnet inference onnxTNN - TNN: developed by Tencent Youtu Lab and Guangying Lab, a uniform deep learning inference framework for mobile、desktop and server
TNN: A high-performance, lightweight neural network inference framework open sourced by Tencent Youtu Lab. It also has many outstanding advantages such as cross-platform, high performance, model compression, and code tailoring. The TNN framework further strengthens the support and performance optimization of mobile devices on the basis of the original Rapidnet and ncnn frameworks. At the same time, it refers to the high performance and good scalability characteristics of the industry's mainstream open source frameworks, and expands the support for X86 and NV GPUs. On the mobile phone, TNN has been used by many applications such as mobile QQ, weishi, and Pitu. As a basic acceleration framework for Tencent Cloud AI, TNN has provided acceleration support for the implementation of many businesses. Everyone is welcome to participate in the collaborative construction to promote the further improvement of the TNN reasoning framework. Chinese OCR demo is the TNN implementation of chineseocr_lite project. It is lightweight and supports tilted, rotated and vertical text recognition.
ocr deep-learning tensorflow inference pytorch tengine face-detection tensorrt mnn coreml ncnn openvino hairsegmentaionTurboTransformers - a fast and user-friendly runtime for transformer inference (Bert, Albert, GPT2, Decoders, etc) on CPU and GPU
The WeChat AI open-sourced TurboTransformers with the following characteristics. TurboTransformers has been applied to multiple online BERT service scenarios in Tencent. For example, It brings 1.88x acceleration to the WeChat FAQ service, 2.11x acceleration to the public cloud sentiment analysis service, and 13.6x acceleration to the QQ recommendation system. Moreover, it has already been applied to build services such as Chitchating, Searching, and Recommendation.
nlp gpu decoder machine-translation inference pytorch transformer albert bert roberta gpt2 huggingface-transformersUltra-Light-Fast-Generic-Face-Detector-1MB - 💎1MB lightweight face detection model (1MB轻量级人脸检测模型)
This model is a lightweight facedetection model designed for edge computing devices. The training set is the VOC format data set generated by using the cleaned widerface labels provided by Retinaface in conjunction with the widerface data set (PS: the following test results were obtained by myself, and the results may be partially inconsistent).
arm inference face-detection mnn ncnnamazon-sagemaker-examples - Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker
Example Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using Amazon SageMaker. Amazon SageMaker is a fully managed service for data science and machine learning (ML) workflows. You can use Amazon SageMaker to simplify the process of building, training, and deploying ML models.
training aws data-science machine-learning reinforcement-learning deep-learning examples jupyter-notebook inference sagemaker mlopsTypeDB - A strongly-typed database
TypeDB is a strongly-typed database with a rich and logical type system. TypeDB empowers you to tackle complex problems, and TypeQL is its query language. TypeDB allows you to model your domain based on logical and object-oriented principles. Composed of entity, relationship, and attribute types, as well as type hierarchies, roles, and rules, TypeDB allows you to think higher-level as opposed to join-tables, columns, documents, vertices, edges, and properties.
database graph logic inference knowledge-graph graph-theory graph-database graphdb knowledge-base type-system strongly-typed graph-visualisation relational knowledge-representation reasoning enterprise-knowledge-graph hyper-relational java-databasePyro - Deep universal probabilistic programming with Python and PyTorch
Pyro is a universal probabilistic programming language (PPL) written in Python and supported by PyTorch on the backend. Pyro enables flexible and expressive deep probabilistic modeling, unifying the best of modern deep learning and Bayesian modeling.
pytorch machine-learning bayesian webppl inference probabilistic-programming probabilistic-graphical-models bayesian-inference variational-inference uberForward - A library for high performance deep learning inference on NVIDIA GPUs.
A library for high performance deep learning inference on NVIDIA GPUs.
deep-learning neural-network tensorflow gpu cuda keras inference pytorch forward tensorrt inference-enginegpu-rest-engine - A REST API for Caffe using Docker and Go
This repository shows how to implement a REST server for low-latency image classification (inference) using NVIDIA GPUs. This is an initial demonstration of the GRE (GPU REST Engine) software that will allow you to build your own accelerated microservices. This repository is a demo, it is not intended to be a generic solution that can accept any trained model. Code customization will be required for your use cases.
caffe gpu inference inference-server docker deep-learning
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