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Showing 16 open source projects for "linux android tool"
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whisper.cpp
Port of OpenAI's Whisper model in C/C++
whisper.cpp is a lightweight, C/C++ reimplementation of OpenAI’s Whisper automatic speech recognition (ASR) model—designed for efficient, standalone transcription without external dependencies. The entire high-level implementation of the model is contained in whisper.h and whisper.cpp. The rest of the code is part of the ggml machine learning library. The command downloads the base.en model converted to custom ggml format and runs the inference on all .wav samples in the folder samples.... -
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RWKV Runner
A RWKV management and startup tool, full automation, only 8MB
RWKV (pronounced as RwaKuv) is an RNN with GPT-level LLM performance, which can also be directly trained like a GPT transformer (parallelizable). So it's combining the best of RNN and transformer - great performance, fast inference, fast training, saves VRAM, "infinite" ctxlen, and free text embedding. Moreover it's 100% attention-free. Default configs has enabled custom CUDA kernel acceleration, which is much faster and consumes much less VRAM. If you encounter possible compatibility... -
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ncnn
High-performance neural network inference framework for mobile
ncnn is a high-performance neural network inference computing framework designed specifically for mobile platforms. It brings artificial intelligence right at your fingertips with no third-party dependencies, and speeds faster than all other known open source frameworks for mobile phone cpu. ncnn allows developers to easily deploy deep learning algorithm models to the mobile platform and create intelligent APPs. It is cross-platform and supports most commonly used CNN networks, including... -
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MegEngine
Easy-to-use deep learning framework with 3 key features
...In training, GPU memory usage could go down to one-third at the cost of only one additional line, which enables the DTR algorithm. Gain the lowest memory usage when inferencing a model by leveraging our unique pushdown memory planner. NOTE: MegEngine now supports Python installation on Linux-64bit/Windows-64bit/MacOS(CPU-Only)-10.14+/Android 7+(CPU-Only) platforms with Python from 3.5 to 3.8. On Windows 10 you can either install the Linux distribution through Windows Subsystem for Linux (WSL) or install the Windows distribution directly. Many other platforms are supported for inference. -
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Bolt NLP
Bolt is a deep learning library with high performance
Bolt is a high-performance deep learning inference framework developed by Huawei Noah's Ark Lab. It is designed to optimize and accelerate the deployment of deep learning models across various hardware platforms. Bolt is a light-weight library for deep learning. Bolt, as a universal deployment tool for all kinds of neural networks, aims to automate the deployment pipeline and achieve extreme acceleration. Bolt has been widely deployed and used in many departments of HUAWEI company, such as... -
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LocalAI
The free, Open Source alternative to OpenAI, Claude and others
LocalAI is an open-source platform that allows users to run large language models and other AI systems locally on their own hardware. It acts as a drop-in replacement for APIs such as OpenAI, enabling developers to build AI-powered applications without relying on external cloud services. The platform supports a wide range of model types, including text generation, image creation, speech processing, and embeddings. LocalAI can run on consumer-grade hardware and does not necessarily require a... -
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OpenVINO
OpenVINO™ Toolkit repository
OpenVINO™ is an open-source toolkit for optimizing and deploying AI inference. Boost deep learning performance in computer vision, automatic speech recognition, natural language processing and other common tasks. Use models trained with popular frameworks like TensorFlow, PyTorch and more. Reduce resource demands and efficiently deploy on a range of Intel® platforms from edge to cloud. This open-source version includes several components: namely Model Optimizer, OpenVINO™ Runtime,... -
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RamaLama
Simplifies the local serving of AI models from any source
RamaLama is an open-source developer tool that simplifies working with and serving AI models locally or in production by leveraging container technologies like Docker, Podman, and OCI registries, allowing AI inference workflows to be treated like standard container deployments. It abstracts away much of the complexity of configuring AI runtimes, dependencies, and hardware optimizations by detecting available GPUs (or falling back to CPU) and automatically pulling a container image... -
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AutoGen
An Open-Source Programming Framework for Agentic AI
AutoGen is an open-source programming framework for building AI agents and facilitating cooperation among multiple agents to solve tasks. AutoGen aims to provide an easy-to-use and flexible framework for accelerating development and research on agentic AI, like PyTorch for Deep Learning. It offers features such as agents that can converse with other agents, LLM and tool use support, autonomous and human-in-the-loop workflows, and multi-agent conversation patterns. AutoGen provides... -
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Sagify
LLMs and Machine Learning done easily
Sagify is a tool designed to simplify the process of deploying and managing machine learning models, including Large Language Models (LLMs), on AWS SageMaker. It abstracts the complexities involved in setting up and managing SageMaker resources, allowing developers to focus on building and fine-tuning models. Sagify provides a command-line interface (CLI) and supports various machine-learning frameworks, making it accessible for a wide range of users. -
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Bard API
The unofficial python package that returns response of Google Bard
The Python package returns a response of Google Bard through the value of the cookie. This package is designed for application to the Python package ExceptNotifier and Co-Coder. Please note that the bardapi is not a free service, but rather a tool provided to assist developers with testing certain functionalities due to the delayed development and release of Google Bard's API. It has been designed with a lightweight structure that can easily adapt to the emergence of an official API.... -
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TensorFlow Model Optimization Toolkit
A toolkit to optimize ML models for deployment for Keras & TensorFlow
The TensorFlow Model Optimization Toolkit is a suite of tools for optimizing ML models for deployment and execution. Among many uses, the toolkit supports techniques used to reduce latency and inference costs for cloud and edge devices (e.g. mobile, IoT). Deploy models to edge devices with restrictions on processing, memory, power consumption, network usage, and model storage space. Enable execution on and optimize for existing hardware or new special purpose accelerators. Choose the model... -
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pipeless
A computer vision framework to create and deploy apps in minutes
Pipeless is an open-source computer vision framework to create and deploy applications without the complexity of building and maintaining multimedia pipelines. It ships everything you need to create and deploy efficient computer vision applications that work in real-time in just minutes. Pipeless is inspired by modern serverless technologies. It provides the development experience of serverless frameworks applied to computer vision. You provide some functions that are executed for new... -
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KotlinDL
High-level Deep Learning Framework written in Kotlin
KotlinDL is a high-level Deep Learning API written in Kotlin and inspired by Keras. Under the hood, it uses TensorFlow Java API and ONNX Runtime API for Java. KotlinDL offers simple APIs for training deep learning models from scratch, importing existing Keras and ONNX models for inference, and leveraging transfer learning for tailoring existing pre-trained models to your tasks. This project aims to make Deep Learning easier for JVM and Android developers and simplify deploying deep learning... -
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MACE
Deep learning inference framework optimized for mobile platforms
Mobile AI Compute Engine (or MACE for short) is a deep learning inference framework optimized for mobile heterogeneous computing on Android, iOS, Linux and Windows devices. Runtime is optimized with NEON, OpenCL and Hexagon, and Winograd algorithm is introduced to speed up convolution operations. The initialization is also optimized to be faster. Chip-dependent power options like big.LITTLE scheduling, Adreno GPU hints are included as advanced APIs. UI responsiveness guarantee is sometimes obligatory when running a model. ... -
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TNN
Uniform deep learning inference framework for mobile
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...
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