Showing 14 open source projects for "convert python to c"

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  • 1
    GPT4All

    GPT4All

    Run Local LLMs on Any Device. Open-source

    .... This project also supports Python integrations for easy automation and customization. GPT4All is ideal for individuals and businesses seeking private, offline access to powerful LLMs.
    Downloads: 91 This Week
    Last Update:
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  • 2
    llama.cpp

    llama.cpp

    Port of Facebook's LLaMA model in C/C++

    The llama.cpp project enables the inference of Meta's LLaMA model (and other models) in pure C/C++ without requiring a Python runtime. It is designed for efficient and fast model execution, offering easy integration for applications needing LLM-based capabilities. The repository focuses on providing a highly optimized and portable implementation for running large language models directly within C/C++ environments.
    Downloads: 67 This Week
    Last Update:
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  • 3
    MegEngine

    MegEngine

    Easy-to-use deep learning framework with 3 key features

    .... 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.
    Downloads: 5 This Week
    Last Update:
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  • 4
    Transformer Engine

    Transformer Engine

    A library for accelerating Transformer models on NVIDIA GPUs

    Transformer Engine (TE) is a library for accelerating Transformer models on NVIDIA GPUs, including using 8-bit floating point (FP8) precision on Hopper GPUs, to provide better performance with lower memory utilization in both training and inference. TE provides a collection of highly optimized building blocks for popular Transformer architectures and an automatic mixed precision-like API that can be used seamlessly with your framework-specific code. TE also includes a framework-agnostic C++ API...
    Downloads: 4 This Week
    Last Update:
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  • 5
    Lepton AI

    Lepton AI

    A Pythonic framework to simplify AI service building

    A Pythonic framework to simplify AI service building. Cutting-edge AI inference and training, unmatched cloud-native experience, and top-tier GPU infrastructure. Ensure 99.9% uptime with comprehensive health checks and automatic repairs.
    Downloads: 2 This Week
    Last Update:
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  • 6
    PaddleSpeech

    PaddleSpeech

    Easy-to-use Speech Toolkit including Self-Supervised Learning model

    PaddleSpeech is an open-source toolkit on PaddlePaddle platform for a variety of critical tasks in speech and audio, with state-of-art and influential models. Via the easy-to-use, efficient, flexible and scalable implementation, our vision is to empower both industrial application and academic research, including training, inference & testing modules, and deployment process. Low barriers to install, CLI, Server, and Streaming Server is available to quick-start your journey. We provide...
    Downloads: 3 This Week
    Last Update:
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  • 7
    OpenVINO Training Extensions

    OpenVINO Training Extensions

    Trainable models and NN optimization tools

    OpenVINO™ Training Extensions provide a convenient environment to train Deep Learning models and convert them using the OpenVINO™ toolkit for optimized inference. When ote_cli is installed in the virtual environment, you can use the ote command line interface to perform various actions for templates related to the chosen task type, such as running, training, evaluating, exporting, etc. ote train trains a model (a particular model template) on a dataset and saves results in two files. ote...
    Downloads: 2 This Week
    Last Update:
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  • 8
    CTranslate2

    CTranslate2

    Fast inference engine for Transformer models

    CTranslate2 is a C++ and Python library for efficient inference with Transformer models. The project implements a custom runtime that applies many performance optimization techniques such as weights quantization, layers fusion, batch reordering, etc., to accelerate and reduce the memory usage of Transformer models on CPU and GPU. The execution is significantly faster and requires less resources than general-purpose deep learning frameworks on supported models and tasks thanks to many advanced...
    Downloads: 3 This Week
    Last Update:
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  • 9
    ChatGLM.cpp

    ChatGLM.cpp

    C++ implementation of ChatGLM-6B & ChatGLM2-6B & ChatGLM3 & GLM4(V)

    ChatGLM.cpp is a C++ implementation of the ChatGLM-6B model, enabling efficient local inference without requiring a Python environment. It is optimized for running on consumer hardware.
    Downloads: 1 This Week
    Last Update:
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  • 10
    rwkv.cpp

    rwkv.cpp

    INT4/INT5/INT8 and FP16 inference on CPU for RWKV language model

    Besides the usual FP32, it supports FP16, quantized INT4, INT5 and INT8 inference. This project is focused on CPU, but cuBLAS is also supported. RWKV is a novel large language model architecture, with the largest model in the family having 14B parameters. In contrast to Transformer with O(n^2) attention, RWKV requires only state from the previous step to calculate logits. This makes RWKV very CPU-friendly on large context lengths.
    Downloads: 1 This Week
    Last Update:
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  • 11
    OpenMLDB

    OpenMLDB

    OpenMLDB is an open-source machine learning database

    ... and inference. Real-time features are essential for many machine learning applications, such as real-time personalized recommendations and risk analytics. However, a feature engineering script developed by data scientists (Python scripts in most cases) cannot be directly deployed into production for online inference because it usually cannot meet the engineering requirements, such as low latency, high throughput and high availability.
    Downloads: 0 This Week
    Last Update:
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  • 12
    DALI

    DALI

    A GPU-accelerated library containing highly optimized building blocks

    The NVIDIA Data Loading Library (DALI) is a library for data loading and pre-processing to accelerate deep learning applications. It provides a collection of highly optimized building blocks for loading and processing image, video and audio data. It can be used as a portable drop-in replacement for built-in data loaders and data iterators in popular deep learning frameworks. Deep learning applications require complex, multi-stage data processing pipelines that include loading, decoding,...
    Downloads: 0 This Week
    Last Update:
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  • 13
    AI Chatbots based on GPT Architecture

    AI Chatbots based on GPT Architecture

    Training & Implementation of chatbots leveraging GPT-like architecture

    Training & Implementation of chatbots leveraging GPT-like architecture with the aitextgen package to enable dynamic conversations. It sure seems like there are a lot of text-generation chatbots out there, but it's hard to find a python package or model that is easy to tune around a simple text file of message data. This repo is a simple attempt to help solve that problem. ai-msgbot covers the practical use case of building a chatbot that sounds like you (or some dataset/persona you choose...
    Downloads: 0 This Week
    Last Update:
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  • 14
    Hello AI World

    Hello AI World

    Guide to deploying deep-learning inference networks

    Hello AI World is a great way to start using Jetson and experiencing the power of AI. In just a couple of hours, you can have a set of deep learning inference demos up and running for realtime image classification and object detection on your Jetson Developer Kit with JetPack SDK and NVIDIA TensorRT. The tutorial focuses on networks related to computer vision, and includes the use of live cameras. You’ll also get to code your own easy-to-follow recognition program in Python or C++, and train...
    Downloads: 0 This Week
    Last Update:
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