Search Results for "suicide-linux" - Page 86

Showing 16387 open source projects for "suicide-linux"

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  • 1
    Numba CUDA Target

    Numba CUDA Target

    The CUDA target for Numba

    Numba CUDA Target is NVIDIA’s maintained CUDA backend for the Numba JIT compiler, enabling developers to write GPU-accelerated code directly in Python. It allows users to define CUDA kernels using Python syntax, which are then compiled into efficient GPU code at runtime using LLVM-based toolchains. This approach significantly lowers the barrier to entry for GPU programming by eliminating the need to write CUDA C++ while still delivering high performance. The project supports the SIMT...
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  • 2
    TensorRT LLM

    TensorRT LLM

    TensorRT LLM provides users with an easy-to-use Python API

    TensorRT-LLM is an open-source high-performance inference library specifically designed to optimize and accelerate large language model deployment on NVIDIA GPUs. It provides a Python-based API built on top of PyTorch that allows developers to define, customize, and deploy LLMs efficiently across a variety of hardware configurations, from single GPUs to large multi-node clusters. The library focuses on maximizing throughput and minimizing latency through advanced techniques such as...
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  • 3
    LitServe

    LitServe

    Minimal Python framework for scalable AI inference servers fast

    LitServe is a minimal Python framework designed for building custom AI inference servers with full control over how models are executed and served. It allows developers to define their own inference logic, making it suitable for complex systems such as multi-model pipelines, agents, and retrieval-augmented generation workflows. Unlike traditional serving tools that enforce rigid abstractions, LitServe focuses on flexibility by letting users control request handling, batching strategies, and...
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  • 4
    Cognita

    Cognita

    Open source RAG framework for building scalable modular AI apps

    Cognita is an open source framework designed to help developers build, organize, and deploy Retrieval-Augmented Generation (RAG) applications in a structured and production-ready way. It addresses the gap between quick experimentation in notebooks and the complexity of deploying scalable AI systems by introducing a modular and API-driven architecture. Cognita provides reusable components such as parsers, data loaders, embedders, retrievers, and query controllers, allowing teams to customize...
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  • 5
    ComfyUI-Copilot

    ComfyUI-Copilot

    AI assistant for ComfyUI workflow generation, debugging, and tuning

    ComfyUI-Copilot is an AI-powered assistant designed to extend the capabilities of ComfyUI by simplifying and automating complex workflow development tasks. It functions as a custom node integrated directly into the ComfyUI environment, allowing users to interact with workflows through natural language and intelligent suggestions. ComfyUI-Copilot focuses on reducing the complexity of building node-based pipelines for generative AI tasks such as image generation, making it more accessible to...
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  • 6
    Kiln

    Kiln

    Open source platform for managing, testing, and deploying AI apps

    Kiln is an open source platform designed to help developers build, evaluate, and deploy AI-powered applications with greater structure and reliability. It provides a unified environment for managing prompts, datasets, and evaluation workflows, allowing teams to iterate on AI behavior in a controlled and measurable way. Kiln emphasizes reproducibility, enabling users to track changes to prompts and models while comparing outputs across different configurations. Kiln also supports systematic...
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  • 7
    Google Kubernetes Engine (GKE) Samples

    Google Kubernetes Engine (GKE) Samples

    Sample applications for Google Kubernetes Engine (GKE)

    Google Kubernetes Engine (GKE) Samples repository is a comprehensive collection of sample applications and reference implementations designed to demonstrate how to build, deploy, and manage workloads on Google Kubernetes Engine (GKE). It serves as a practical companion to official GKE tutorials, providing real, runnable code that illustrates how containerized applications are packaged, deployed, and scaled within Kubernetes clusters. The repository is organized into multiple categories such...
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  • 8
    OpenHome Abilities

    OpenHome Abilities

    Open-source abilities for OpenHome agents

    OpenHome Abilities is an open-source repository of modular voice AI plugins created for OpenHome agents, giving developers a lightweight way to extend what an agent can do through spoken triggers. Each ability is intentionally simple in structure, centering on a single main.py file that contains the core Python logic, which lowers the barrier to building and sharing custom behaviors. The system is meant to support a wide range of voice-driven actions, from API calls and media playback to...
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  • 9
    dots.ocr

    dots.ocr

    Multilingual Document Layout Parsing in a Single Vision-Language Model

    dots.ocr is a cutting-edge multilingual document parsing system built on a unified vision-language model that combines layout detection, text recognition, and structural understanding into a single architecture. Unlike traditional OCR pipelines that rely on multiple specialized components, dots.ocr integrates these processes end-to-end, reducing error propagation and improving consistency across tasks. The model is designed to recognize virtually any human script, making it highly effective...
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  • 10
    PySpur

    PySpur

    Visual tool for building, testing, and deploying AI agent workflows

    PySpur is a visual development environment designed to help AI engineers build, test, and iterate on agent-based workflows more efficiently. It provides a structured playground where users can define test cases, construct agents either through Python code or a graphical interface, and continuously refine their behavior. It addresses common challenges in AI agent development such as prompt tuning difficulties and lack of visibility into workflow execution. By offering a visual representation...
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  • 11
    Swarms

    Swarms

    Enterprise multi-agent orchestration framework for scalable AI apps

    Swarms is an enterprise-grade multi-agent orchestration framework designed to help developers build, manage, and scale collaborative AI systems composed of multiple agents. It provides a structured infrastructure for coordinating agents in hierarchical, parallel, or sequential workflows, enabling complex task execution across distributed components. It emphasizes production readiness, offering modular architecture, high availability, and observability features suitable for large-scale...
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  • 12
    Factorio

    Factorio

    Factorio headless server in a Docker container

    Factorio is an open-source project that provides a Docker container for running a headless Factorio game server. Factorio is a factory-building simulation game in which players automate production lines, research technologies, and manage complex industrial systems, and the repository focuses specifically on hosting the game server in a containerized environment. By packaging the server into a Docker image, the project simplifies the process of deploying and maintaining multiplayer servers...
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  • 13
    TADA

    TADA

    Open Source Speech Language Model

    TADA is an open-source speech-language modeling framework designed to unify spoken audio and text representations within a single generative architecture. The system focuses on aligning speech and text streams using a dual-alignment mechanism that synchronizes the acoustic signal with its textual representation. By modeling both modalities together, the framework allows developers to build systems capable of generating, understanding, and transforming speech and language simultaneously. This...
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  • 14
    PySINDy

    PySINDy

    A package for the sparse identification of nonlinear dynamical systems

    PySINDy is a Python library that implements the Sparse Identification of Nonlinear Dynamics (SINDy) method for discovering mathematical models of dynamical systems from data. The framework focuses on identifying governing equations that describe the behavior of complex physical systems by selecting sparse combinations of candidate functions. Instead of fitting a purely predictive machine learning model, PySINDy attempts to recover interpretable differential equations that explain how a...
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  • 15
    docext

    docext

    An on-premises, OCR-free unstructured data extraction

    docext is a document intelligence toolkit that uses vision-language models to extract structured information from documents such as PDFs, forms, and scanned images. The system is designed to operate entirely on-premises, allowing organizations to process sensitive documents without relying on external cloud services. Unlike traditional document processing pipelines that rely heavily on optical character recognition, docext leverages multimodal AI models capable of understanding both visual...
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  • 16
    SpikingJelly

    SpikingJelly

    SpikingJelly is an open-source deep learning framework

    SpikingJelly is an open-source deep learning framework for spiking neural networks that is primarily built on top of PyTorch and aimed at neuromorphic computing research. The project provides the components needed to build, train, and evaluate neural models that communicate through discrete spikes rather than the continuous activations used in conventional artificial neural networks. This makes it especially relevant for researchers interested in biologically inspired computing, event-driven...
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  • 17
    SimpleHTR

    SimpleHTR

    Handwritten Text Recognition (HTR) system implemented with TensorFlow

    SimpleHTR is an open-source implementation of a handwriting text recognition system based on deep learning techniques. The project focuses on converting images of handwritten text into machine-readable digital text using neural networks. The system uses a combination of convolutional neural networks and recurrent neural networks to extract visual features and model sequential character patterns in handwriting. It also employs connectionist temporal classification (CTC) to align predicted...
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  • 18
    Apache Hamilton

    Apache Hamilton

    Helps data scientists define testable self-documenting dataflows

    Apache Hamilton is an open-source Python framework designed to simplify the creation and management of dataflows used in analytics, machine learning pipelines, and data engineering workflows. The framework enables developers to define data transformations as simple Python functions, where each function represents a node in a dataflow graph and its parameters define dependencies on other nodes. Hamilton automatically analyzes these functions and constructs a directed acyclic graph...
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  • 19
    NVIDIA PhysicsNeMo

    NVIDIA PhysicsNeMo

    Open-source deep-learning framework for building and training

    NVIDIA PhysicsNeMo is an open-source deep learning framework designed for building artificial intelligence models that incorporate physical laws and scientific knowledge into machine learning workflows. The framework focuses on the emerging field of physics-informed machine learning, where neural networks are used alongside physical equations to model complex scientific systems. PhysicsNeMo provides modular Python components that allow developers to create scalable training and inference...
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  • 20
    VoxelMorph

    VoxelMorph

    Unsupervised Learning for Image Registration

    VoxelMorph is an open-source deep learning framework designed for medical image registration, a process that aligns multiple medical scans into a common spatial coordinate system. Traditional image registration techniques typically rely on optimization procedures that must be executed separately for each pair of images, which can be computationally expensive and slow. VoxelMorph approaches the problem using neural networks that learn to predict deformation fields that transform one image so...
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  • 21
    SimpleTuner

    SimpleTuner

    A general fine-tuning kit geared toward image/video/audio diffusion

    SimpleTuner is an open-source toolkit designed to simplify the fine-tuning of modern diffusion models for generating images, video, and audio. The project focuses on providing a clear and understandable training environment for researchers, developers, and artists who want to customize generative AI models without navigating complex machine learning pipelines. It supports fine-tuning workflows for models such as Stable Diffusion variants and other diffusion architectures, enabling users to...
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  • 22
    CUDA Containers for Edge AI & Robotics

    CUDA Containers for Edge AI & Robotics

    Machine Learning Containers for NVIDIA Jetson and JetPack-L4T

    CUDA Containers for Edge AI & Robotics is an open-source project that provides a modular container build system designed for running machine learning and AI workloads on NVIDIA Jetson devices. The repository contains container configurations that package the latest AI frameworks and dependencies optimized for Jetson hardware. These containers simplify the deployment of complex machine learning environments by bundling libraries such as CUDA, TensorRT, and deep learning frameworks into...
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  • 23
    pyAudioAnalysis

    pyAudioAnalysis

    Python Audio Analysis Library: Feature Extraction, Classification

    pyAudioAnalysis is an open-source Python library designed for audio signal analysis, machine learning, and music information retrieval tasks. The project provides a collection of tools that allow developers to extract meaningful features from audio files and use those features for classification, segmentation, and analysis. The library supports multiple audio processing workflows, including feature extraction from raw audio signals, training of machine learning models, and automatic audio...
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  • 24
    Jina-Serve

    Jina-Serve

    Build multimodal AI applications with cloud-native stack

    Jina Serve is an open-source framework designed for building, deploying, and scaling AI services and machine learning pipelines in production environments. The framework allows developers to create microservices that expose machine learning models through APIs that communicate using protocols such as HTTP, gRPC, and WebSockets. It is built with a cloud-native architecture that supports deployment on local machines, containerized environments, or large orchestration platforms such as...
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  • 25
    TTRL

    TTRL

    Test-Time Reinforcement Learning

    TTRL is an open-source framework for test-time reinforcement learning in large language models, with a particular focus on reasoning tasks where ground-truth labels are not available during inference. The project addresses the problem of how to generate useful reward signals from unlabeled test-time data, and its central insight is that common test-time scaling practices such as majority voting can be repurposed into reward estimates for online reinforcement learning. This makes the...
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