Search Results for "open source tv" - Page 95

Showing 16978 open source projects for "open source tv"

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  • 1
    Qwen3-VL-Embedding

    Qwen3-VL-Embedding

    Multimodal embedding and reranking models built on Qwen3-VL

    Qwen3-VL-Embedding (with its companion Qwen3-VL-Reranker) is a state-of-the-art multimodal embedding and reranking model suite built on the open-sourced Qwen3-VL foundation, developed to handle diverse inputs including text, images, screenshots, and videos. The core embedding model maps such inputs into semantically rich vectors in a unified representation space, enabling similarity search, clustering, and cross-modal retrieval. The reranking model then precisely scores relevance between a...
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  • 2
    Anthropic's Original Performance

    Anthropic's Original Performance

    Anthropic's original performance take-home, now open for you to try

    Anthropic's Original Performance repository contains the publicly released version of a performance challenge originally used by Anthropic as part of their technical interview process, offering developers the opportunity to optimize and benchmark low-level code against simulated models. The project sets up a baseline performance problem where participants work to reduce simulated “clock cycles” required to run a given workload, effectively challenging them to engineer faster code under...
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  • 3
    EPLB

    EPLB

    Expert Parallelism Load Balancer

    EPLB is DeepSeek’s open implementation of a load balancing algorithm designed for expert parallelism (EP) settings in MoE architectures. In EP, different “experts” are mapped to different GPUs or nodes, so load imbalance becomes a performance bottleneck if certain experts are invoked much more often. EPLB solves this by duplicating heavily used experts (redundancy) and then placing those duplicates across GPUs to even out computational load. It uses policies like hierarchical load balancing...
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  • 4
    GPT Researcher

    GPT Researcher

    LLM based autonomous agent that does online comprehensive research

    Say Hello to GPT Researcher, your AI agent for rapid insights and comprehensive research. GPT Researcher is the leading autonomous agent that takes care of everything from accurate source gathering to organization of research results.
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  • 5
    Gorilla

    Gorilla

    Gorilla: An API store for LLMs

    Gorilla is Apache 2.0 With Gorilla being fine-tuned on MPT, and Falcon, you can use Gorilla commercially with no obligations. Gorilla enables LLMs to use tools by invoking APIs. Given a natural language query, Gorilla comes up with the semantically- and syntactically- correct API to invoke. With Gorilla, we are the first to demonstrate how to use LLMs to invoke 1,600+ (and growing) API calls accurately while reducing hallucination. We also release APIBench, the largest collection of APIs,...
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  • 6
    Mailu

    Mailu

    Insular email distribution - mail server as Docker images

    Mailu is a simple yet full-featured mail server as a set of Docker images. It is free software (both as in free beer and as in free speech), open to suggestions and external contributions. The project aims at providing people with an easily setup, easily maintained and full-featured mail server while not shipping proprietary software nor unrelated features often found in popular groupware. Security, enforced TLS, DANE, MTA-STS, Letsencrypt!, outgoing DKIM, anti-virus scanner, Snuffleupagus,...
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  • 7
    Cha

    Cha

    Deprecated AI CLI for terminal based interactions

    Cha is a command-line AI assistant for terminal-based interaction with large language models. It was designed to let developers chat with AI from the terminal while keeping control over the workflow and environment. The repository now serves as a historical reference because active development moved to Ch, a faster Go-based successor. Cha included support materials such as optional search setup assets, including SearXNG-related configuration instructions. Its value today is mostly archival,...
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  • 8
    Tile Kernels

    Tile Kernels

    A kernel library written in tilelang

    Tile Kernels is a DeepSeek kernel library written with TileLang for high-performance AI and machine-learning workloads. It contains specialized kernels for areas such as mixture-of-experts routing, quantization, batched transpose operations, Engram gating, and Manifold HyperConnection components. The project includes both optimized kernel implementations and PyTorch reference versions for comparison and validation. It is aimed at developers and researchers who work close to model internals...
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  • 9
    yourself-skill

    yourself-skill

    Instead of distilling others, it is better to distil yourself

    yourself-skill is an AI skill framework focused on self-reflection and personalization, enabling agents to adapt their behavior based on user context and interaction history. It encourages systems to maintain awareness of user preferences, goals, and communication styles. The project emphasizes building more human-aligned interactions by incorporating memory and contextual reasoning. It can be integrated into broader AI systems to improve personalization and continuity across sessions. The...
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  • 10
    cloud-morph

    cloud-morph

    Decentralize, Self-host Cloud Gaming/Application

    cloud-morph is a cloud-based media processing service that enables real-time video and audio transformation using FFmpeg in scalable environments. It is designed to run as a backend service that processes media streams or files and applies transformations such as transcoding, filtering, and format conversion. The system supports API-driven workflows, allowing integration into web applications or automation pipelines. It leverages containerization and distributed architecture to handle...
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  • 11
    pix2pixHD

    pix2pixHD

    Synthesizing and manipulating 2048x1024 images with conditional GANs

    pix2pixHD is a PyTorch-based implementation of a conditional generative adversarial network designed for high-resolution image-to-image translation, capable of producing photorealistic outputs at resolutions up to 2048×1024. It is widely used to convert structured inputs such as semantic label maps into realistic images, making it particularly valuable in applications like autonomous driving simulation, face synthesis, and scene generation. The model improves upon earlier GAN approaches by...
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  • 12
    FAY

    FAY

    Framework for building AI-powered interactive digital humans and agent

    Fay is an open source framework designed to build and deploy interactive digital humans powered by large language models. It acts as a middleware layer that connects digital character technologies with conversational AI systems and business applications. Fay supports various types of digital humans, including 2.5D and 3D avatars, and can be integrated with applications running on mobile devices, PCs, web platforms, and embedded systems.
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  • 13
    Xianyu Intelligent Monitor Bot

    Xianyu Intelligent Monitor Bot

    AI tool for real-time monitoring and analysis of Goofish listings

    ai-goofish-monitor is an open source automation tool designed to monitor listings on the Goofish second-hand marketplace and analyze them using artificial intelligence. It combines browser automation with AI-based analysis to automatically search, collect, and evaluate newly posted items that match a user’s purchase criteria. It uses Playwright to simulate real user interactions with the marketplace, allowing the system to retrieve product data and track updates in near real time. ai-goofish-monitor can run multiple monitoring tasks simultaneously, each configured with specific keywords, price ranges, and filtering conditions. ...
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  • 14
    kg-gen

    kg-gen

    Knowledge Graph Generation from Any Text

    kg-gen is an open-source framework developed by the STAIR Lab that automatically generates knowledge graphs from unstructured text using large language models. The system is designed to transform plain text sources such as documents, articles, or conversation transcripts into structured graphs composed of entities and relationships. Instead of relying on traditional rule-based extraction techniques, KG-Gen uses language models to identify entities and their relationships, producing higher-quality graph structures from raw text. ...
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  • 15
    E2B Cookbook

    E2B Cookbook

    Examples of using E2B

    E2B Cookbook is an open-source collection of example projects, guides, and reference implementations demonstrating how to build applications using the E2B platform. The repository acts as a practical learning resource for developers who want to integrate AI agents with secure cloud execution environments that allow large language models to run code and interact with tools.
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  • 16
    Pal

    Pal

    A personal context-agent that learns how you work

    Pal is an open-source AI personal agent built within the Agno ecosystem that functions as an intelligent digital assistant designed to learn from user activity over time. The system acts as an AI-powered “second brain” capable of capturing, organizing, and retrieving personal knowledge such as notes, bookmarks, research findings, people, and meeting information.
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  • 17
    handy-ollama

    handy-ollama

    Implement CPU from scratch and play with large model deployments

    handy-ollama is an open-source educational project designed to help developers and AI enthusiasts learn how to deploy and run large language models locally using the Ollama platform. The repository serves as a structured tutorial that explains how to install, configure, and use Ollama to run modern language models on personal hardware without requiring advanced infrastructure.
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  • 18
    ERNIE

    ERNIE

    The official repository for ERNIE 4.5 and ERNIEKit

    ERNIE is an open-source large-model toolkit and model family from the PaddlePaddle ecosystem that focuses on training, fine-tuning, compression, and practical application of ERNIE large language models. The repository positions ERNIEKit as an industrial-grade development toolkit, emphasizing end-to-end workflows that span high-performance pre-training, supervised fine-tuning, and alignment.
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  • 19
    Modular Platform

    Modular Platform

    The Modular Platform (includes MAX & Mojo)

    Modular is a high-performance AI infrastructure company repository focused on building next-generation compute and software tools for machine learning workloads. The project centers on enabling developers to run AI models faster and more efficiently by rethinking the traditional ML software stack. It is closely associated with the Mojo programming language and related tooling that aims to combine Python usability with systems-level performance. Modular’s ecosystem is designed to simplify...
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  • 20
    Claude Quickstarts

    Claude Quickstarts

    A collection of projects for building deployable applications

    Claude Quickstarts is a curated collection of starter projects and templates that help developers quickly begin building applications with the Claude API, making it easier to leverage Anthropic’s Claude models for real use cases. Each quickstart provides a foundational codebase with preconfigured settings and examples for common deployment scenarios, so developers can focus on customizing functionality instead of bootstrapping infrastructure. The repository includes demos, sample...
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  • 21
    Fara-7B

    Fara-7B

    An Efficient Agentic Model for Computer Use

    Fara-7B is a Microsoft initiative aimed at bringing rigor, transparency, and structured evaluation to AI systems through automated and customizable assessment frameworks. It provides stakeholders with a way to benchmark and evaluate models across dimensions such as fairness, robustness, security, privacy, and ethical considerations. Rather than relying on ad-hoc or manual review processes, FARA enables organizations to profile AI behavior using standardized tests, metrics, and reporting...
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  • 22
    InfiAgent

    InfiAgent

    Build your own Cowork, AI Scientist and other SoTA Agents

    infiAgent is an open-source AI agent framework for building powerful, long-running autonomous agents capable of tackling complex tasks without collapsing under growing context or tool invocation histories. Designed as a “Multi-Level Agent” (MLA) system, it externalizes persistent state to the file system so that agents can operate over unlimited runtime without the need for token-intensive context compression, enabling workflows such as research paper drafting, experiments, coding, and document generation to run reliably. ...
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  • 23
    IQuest-Coder-V1 Model Family

    IQuest-Coder-V1 Model Family

    New family of code large language models (LLMs)

    IQuest-Coder-V1 is a cutting-edge family of open-source large language models specifically engineered for code generation, deep code understanding, and autonomous software engineering tasks. These models range from tens of billions to smaller footprints and are trained on a novel code-flow multi-stage paradigm that captures how real software evolves over time — not just static code snapshots — giving them a deeper semantic understanding of programming logic.
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  • 24
    MAI-UI

    MAI-UI

    Real-World Centric Foundation GUI Agents

    MAI-UI is a cutting-edge open-source project that implements a family of foundation GUI (Graphical User Interface) agent models capable of interpreting natural language and performing real-world GUI navigation and control tasks across mobile and desktop environments. Developed by Tongyi-MAI (Alibaba’s research initiative), the MAI-UI models are multimodal agents trained to understand user instructions and corresponding screenshots, grounding those instructions to on-screen elements and generating sequences of GUI actions such as taps, swipes, text input, and system commands. ...
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  • 25
    ESPnet

    ESPnet

    End-to-end speech processing toolkit

    ESPnet is a comprehensive end-to-end speech processing toolkit covering a wide spectrum of tasks, including automatic speech recognition (ASR), text-to-speech (TTS), speech translation (ST), speech enhancement, speaker diarization, and spoken language understanding. It uses PyTorch as its deep learning engine and adopts a Kaldi-style data processing pipeline for features, data formats, and experimental recipes. This combination allows researchers to leverage modern neural architectures while...
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