Search Results for "compiler python to exe"
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Showing 29 open source projects for "compiler python to exe"
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1
GPT Computer Assistant
gpt-4o for windows, macos and linux
This is an alternative work for providing ChatGPT MacOS app to Windows and Linux. In this way, this is a fresh and stable work. You can easily install as a Python library for this time but we will prepare a pipeline for providing native install scripts (.exe). -
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Torch-TensorRT
PyTorch/TorchScript/FX compiler for NVIDIA GPUs using TensorRT
Torch-TensorRT is a compiler for PyTorch/TorchScript, targeting NVIDIA GPUs via NVIDIA’s TensorRT Deep Learning Optimizer and Runtime. Unlike PyTorch’s Just-In-Time (JIT) compiler, Torch-TensorRT is an Ahead-of-Time (AOT) compiler, meaning that before you deploy your TorchScript code, you go through an explicit compile step to convert a standard TorchScript program into a module targeting a TensorRT engine. Torch-TensorRT operates as a PyTorch extension and compiles modules that integrate... -
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MLC LLM
Universal LLM Deployment Engine with ML Compilation
MLC LLM is a machine learning compiler and deployment framework designed to enable efficient execution of large language models across a wide range of hardware platforms. The project focuses on compiling models into optimized runtimes that can run natively on devices such as GPUs, mobile processors, browsers, and edge hardware. By leveraging machine learning compilation techniques, mlc-llm produces high-performance inference engines that maintain consistent APIs across platforms. The system... -
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APKiD
Android Application Identifier for Packers, Protectors and Obfuscators
APKiD gives you information about how an APK was made. It identifies many compilers, packers, obfuscators, and other weird stuff. It's PEiD for Android. -
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Jittor
Jittor is a high-performance deep learning framework
Jittor is a high-performance deep learning framework based on JIT compiling and meta-operators. The whole framework and meta-operators are compiled just in time. A powerful op compiler and tuner are integrated into Jittor. It allowed us to generate high-performance code specialized for your model. Jittor also contains a wealth of high-performance model libraries, including image recognition, detection, segmentation, generation, differentiable rendering, geometric learning, reinforcement learning, etc. The front-end language is Python. ... -
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tvm
Open deep learning compiler stack for cpu, gpu, etc.
...Compilation of deep learning models in Keras, MXNet, PyTorch, Tensorflow, CoreML, DarkNet and more. Start using TVM with Python today, build out production stacks using C++, Rust, or Java the next day. -
7
LLMCompiler
An LLM Compiler for Parallel Function Calling
LLMCompiler is an open-source framework designed to optimize how large language models orchestrate multiple external tool or function calls during complex reasoning tasks. Traditional LLM agent systems typically execute tool calls sequentially, which can create latency, higher costs, and reduced reliability when solving multi-step problems. LLMCompiler addresses this limitation by applying principles from classical compilers to analyze a task and construct an execution plan that allows... -
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BetaML.jl
Beta Machine Learning Toolkit
...Thanks to its JIT compiler, Julia is indeed in the sweet spot where we can easily write models in a high-level language and still have them running efficiently. -
9
AWS Neuron
Powering Amazon custom machine learning chips
AWS Neuron is a software development kit (SDK) for running machine learning inference using AWS Inferentia chips. It consists of a compiler, run-time, and profiling tools that enable developers to run high-performance and low latency inference using AWS Inferentia-based Amazon EC2 Inf1 instances. Using Neuron developers can easily train their machine learning models on any popular framework such as TensorFlow, PyTorch, and MXNet, and run it optimally on Amazon EC2 Inf1 instances. You can... -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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MathCode
A Frontier Mathematical Coding Agent
MathCode is a terminal-based AI coding assistant focused on mathematical formalization and theorem proving. It is designed to transform plain-language mathematical reasoning into verified Lean 4 code and formal proofs. The project combines AI agents with Lean Language Server Protocol integration, allowing it to inspect compiler feedback, search for lemmas, and iteratively repair failed proof attempts. It supports an agentic proving workflow where the system behaves more like an interactive... -
11
Eris
A NodeJS Discord library
A Node.js wrapper for interfacing with Discord. You will need NodeJS 10.4+. If you need voice support you will also need Python 2.7 and a C++ compiler. Create a directory for your bot, and change to that directory in your command line. If you want to be more updated (at the expense of stability), you can install the beta builds instead. Eris supports a few optional libraries that could potentially improve bot performance but may require additional dependencies. -
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CUDA Agent
Large-Scale Agentic RL for High-Performance CUDA Kernel Generation
CUDA Agent is a research-driven agentic reinforcement learning system designed to automatically generate and optimize high-performance CUDA kernels for GPU workloads. The project addresses the long-standing challenge that efficient CUDA programming typically requires deep hardware expertise by training an autonomous coding agent capable of iterative improvement through execution feedback. Its architecture combines large-scale data synthesis, a skill-augmented CUDA development environment,... -
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PyTorch/XLA
Enabling PyTorch on Google TPU
PyTorch/XLA is a Python package that uses the XLA deep learning compiler to connect the PyTorch deep learning framework and Cloud TPUs. You can try it right now, for free, on a single Cloud TPU with Google Colab, and use it in production and on Cloud TPU Pods with Google Cloud. Take a look at one of our Colab notebooks to quickly try different PyTorch networks running on Cloud TPUs and learn how to use Cloud TPUs as PyTorch devices. -
14
Whisper Batch Transcriber
Unlimited, private and free Speech-To-Text program
.... ## Notes: - Its 2GB in size and requires 2-6GB of GPU VRAM too. (basically you need atleast a mid-range gaming PC to use this.) - Its fairly slow to start (10min) and transcribe, this is normal behavior. - Includes a python installer to install Python on your computer so you can directly run the 'whisper_transcriber.py' file like you would an .exe by double-clicking it. (I did this because compiling to exe made it slower) - I made it as easy as possible for a layperson to use, so despite its crude looks, its as good as a GUI application experience. ... -
15
torchtext
Data loaders and abstractions for text and NLP
We recommend Anaconda as a Python package management system. Please refer to pytorch.org for the details of PyTorch installation. LTS versions are distributed through a different channel than the other versioned releases. Alternatively, you might want to use the Moses tokenizer port in SacreMoses (split from NLTK). You have to install SacreMoses. To build torchtext from source, you need git, CMake and C++11 compiler such as g++. -
16
Programming Without Coding Technology
Create software using visual programming
...PWCT support Harbour, Supernova, C, Python, & C#.NET and you can extend PWCT to support code generation in any text based programming language. PWCT comes with many samples, tutorials and movies. -
17
OneFlow
OneFlow is a deep learning framework designed to be user-friendly
OneFlow is a deep learning framework designed to be user-friendly, scalable and efficient. An extension for OneFlow to target third-party compiler, such as XLA, TensorRT and OpenVINO etc.CUDA runtime is statically linked into OneFlow. OneFlow will work on a minimum supported driver, and any driver beyond. For more information. Distributed performance (efficiency) is the core technical difficulty of the deep learning framework. OneFlow focuses on performance improvement and heterogeneous... -
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AI System & AI Infra
Tutorial repository focused on the full-stack design of AI systems
AI System is an educational and technical tutorial repository focused on the full-stack design of artificial intelligence systems, covering the foundational infrastructure that powers modern deep learning workloads. The project explores the AI software and hardware stack end to end, including AI chips, AI compilers, inference engines, and training frameworks, helping learners understand how these components interact in real-world deployments. Rather than being a single library, it functions... -
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macara
A converter for seamless transformation of files, data, and media ...
This application consolidates various scripts, including an AI feature (rembg), into a singular platform. The design of this software is evolutionary, allowing for the seamless integration of additional scripts, menus, or windows as needed. Serving as a versatile tool, it facilitates efficient file management, especially when handling a substantial volume of images, whether sorting by name or other attributes. These scripts are crafted to complement generative art AI technologies like Dall-e... -
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Bullet Physics SDK
Real-time collision detection and multi-physics simulation for VR
This is the official C++ source code repository of the Bullet Physics SDK: real-time collision detection and multi-physics simulation for VR, games, visual effects, robotics, machine learning etc. We are developing a new differentiable simulator for robotics learning, called Tiny Differentiable Simulator, or TDS. The simulator allows for hybrid simulation with neural networks. It allows different automatic differentiation backends, for forward and reverse mode gradients. TDS can be trained... -
21
Swift for TensorFlow
Swift for TensorFlow
Swift for TensorFlow repository contains the open-source implementation of Swift for TensorFlow, a project that integrates machine learning capabilities directly into the Swift programming language. The initiative aims to provide a new programming model for developing machine learning systems by combining the power of TensorFlow with language-level features such as automatic differentiation and strong type systems. By embedding machine learning functionality into the Swift compiler and... -
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DeepMind Lab
A customizable 3D platform for agent-based AI research
...Its primary purpose is to act as a testbed for research in artificial intelligence, especially deep reinforcement learning. If you use DeepMind Lab in your research and would like to cite the DeepMind Lab environment, we suggest you cite the DeepMind Lab paper. To enable compiler optimizations, pass the flag --compilation_mode=opt, or -c opt for short, to each bazel build, bazel test and bazel run command. The flag is omitted from the examples here for brevity, but it should be used for real training and evaluation where performance matters. DeepMind Lab ships with an example random agent in python/random_agent.py which can be used as a starting point for implementing a learning agent. -
23
SQLFlow
SQL compiler bridging databases and machine learning workflows
SQLFlow is an open source project designed to bridge the gap between traditional SQL-based data processing and modern machine learning workflows by extending SQL syntax with AI capabilities. It acts as a compiler that translates SQL programs into executable workflows, enabling users to train, evaluate, and deploy machine learning models directly from SQL statements. It integrates with multiple database engines such as MySQL, Hive, and MaxCompute, while also supporting machine learning frameworks like TensorFlow and XGBoost. By embedding machine learning operations into SQL, it removes the need for users to switch between programming languages such as Python or R, simplifying the overall workflow. ... -
24
nGraph
nGraph has moved to OpenVINO
Frameworks using nGraph Compiler stack to execute workloads have shown up to 45X performance boost when compared to native framework implementations. We've also seen performance boosts running workloads that are not included on the list of Validated workloads, thanks to nGraph's powerful subgraph pattern matching. Additionally, we have integrated nGraph with PlaidML to provide deep learning performance acceleration on Intel, nVidia, & AMD GPUs. nGraph Compiler aims to accelerate developing... -
25
lgo
Interactive Go programming with Jupyter
...The system supports the full Go language specification and works directly with the standard Go compiler, ensuring compatibility with typical Go development practices. In addition to running code interactively, lgo supports advanced notebook capabilities such as code completion, inspection tools, and rendering of multimedia outputs.
