Showing 811 open source projects for "quality"

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  • 1
    DeepSeek-V3

    DeepSeek-V3

    Powerful AI language model (MoE) optimized for efficiency/performance

    ...The model introduces an auxiliary-loss-free load balancing strategy and a multi-token prediction training objective to boost performance. Trained on 14.8 trillion diverse, high-quality tokens, DeepSeek-V3 underwent supervised fine-tuning and reinforcement learning to fully realize its capabilities. Evaluations indicate that it outperforms other open-source models and rivals leading closed-source models, achieving this with a training duration of 55 days on 2,048 Nvidia H800 GPUs, costing approximately $5.58 million.
    Downloads: 66 This Week
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  • 2
    Oppia

    Oppia

    A free, online learning platform to make quality education accessible

    Oppia is an online learning tool that enables anyone to easily create and share interactive activities (called 'explorations'). These activities simulate a one-on-one conversation with a tutor, making it possible for students to learn by doing while getting feedback. Oppia identifies common wrong answers and provides tailored feedback, so that students get a personalized experience. Our lessons keep students engaged through playful characters and use different strategies to solidify their...
    Downloads: 0 This Week
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  • 3
    LatentSync

    LatentSync

    Taming Stable Diffusion for Lip Sync

    LatentSync is an open-source framework from ByteDance that produces high-quality lip-synchronization for video by using an audio-conditioned latent diffusion model, bypassing traditional intermediate motion representations. In effect, given a source video (with masked or reference frames) and an audio track, LatentSync directly generates frames whose lip motions and expressions align with the audio, producing convincing talking-head or animated lip-sync output.
    Downloads: 3 This Week
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  • 4
    n8n Workflows

    n8n Workflows

    All of the workflows of n8n i could find (also from the site itself)

    ...It serves as an index for discovering ready-made flows to automate tasks across multiple services and platforms. 2,057 workflows with meaningful, searchable names. 365 unique integrations across popular platforms. 29,445 total nodes with professional categorization. Quality assurance - All workflows analyzed and categorized.
    Downloads: 7 This Week
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  • 5
    AI Marketing Skills

    AI Marketing Skills

    Open-source AI marketing skills for Claude Code

    ...The system is organized into multiple domains such as growth experimentation, sales pipeline generation, content production, outbound marketing, SEO optimization, and financial analysis, effectively covering the entire revenue lifecycle of a business. Each skill functions as an executable capability that can be invoked on demand, enabling users to perform tasks like running A/B tests, generating high-quality content, or analyzing conversion funnels with minimal manual effort.
    Downloads: 2 This Week
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  • 6
    Diffusers

    Diffusers

    State-of-the-art diffusion models for image and audio generation

    ...State-of-the-art diffusion pipelines that can be run in inference with just a few lines of code. Interchangeable noise schedulers for different diffusion speeds and output quality. Pretrained models that can be used as building blocks, and combined with schedulers, for creating your own end-to-end diffusion systems. We recommend installing Diffusers in a virtual environment from PyPi or Conda. For more details about installing PyTorch and Flax, please refer to their official documentation.
    Downloads: 2 This Week
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  • 7
    nbmake

    nbmake

    Pytest plugin for testing notebooks

    Pytest plugin for testing and releasing notebook documentation. To raise the quality of scientific material through better automation. Research/Machine Learning Software Engineers who maintain packages/teaching materials with documentation written in notebooks.
    Downloads: 5 This Week
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  • 8
    DeepVariant

    DeepVariant

    DeepVariant is an analysis pipeline that uses a deep neural networks

    ...DeepTrio extends DeepVariant's functionality, allowing it to utilize the power of neural networks to predict genomic variants in trios or duos. See this page for more details and instructions on how to run DeepTrio. Out-of-the-box use for PCR-positive samples and low quality sequencing runs, and easy adjustments for different sequencing technologies and non-human species.
    Downloads: 1 This Week
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  • 9
    PasteMD

    PasteMD

    Paste Markdown and AI responses into Word Excel instantly fast

    PasteMD is a lightweight desktop utility designed to streamline the process of transferring formatted content from the clipboard into office applications such as Word, WPS, and Excel. It primarily targets users who frequently copy content from AI chat tools or web pages and encounter formatting issues, especially with Markdown, tables, and LaTeX formulas. PasteMD operates from the system tray and monitors clipboard content, automatically converting Markdown or HTML into properly formatted...
    Downloads: 23 This Week
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  • 10
    SeedVR

    SeedVR

    Repo for SeedVR2 & SeedVR

    SeedVR (from the ByteDance-Seed organization) is an open-source research and implementation repository focused on cutting-edge video restoration using diffusion transformer architectures. The project includes both the original SeedVR and its successor SeedVR2 models, which are designed to restore degraded or low-quality video content by learning to reconstruct high-fidelity frames with temporal coherence. These models leverage advanced techniques such as adaptive attention mechanisms and adversarial training to produce visually appealing results in a single inference step, pushing the boundaries of video restoration research. SeedVR’s transformer-based design allows it to handle variable frame resolutions and lengths, and its architecture is optimized to overcome traditional limitations of windowed attention in high-resolution contexts.
    Downloads: 0 This Week
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  • 11
    PyMuPDF

    PyMuPDF

    Python bindings for MuPDF's rendering library.

    MuPDF is a lightweight PDF, XPS, and E-book viewer. MuPDF consists of a software library, command line tools, and viewers for various platforms. The renderer in MuPDF is tailored for high-quality anti-aliased graphics. It renders text with metrics and spacing accurate to within fractions of a pixel for the highest fidelity in reproducing the look of a printed page on the screen. The viewer is small, fast, yet complete. It supports many document formats, such as PDF, XPS, OpenXPS, CBZ, EPUB, and FictionBook 2. You can annotate PDF documents and fill out forms with the mobile viewers (this feature is coming soon to the desktop viewer as well). ...
    Downloads: 22 This Week
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  • 12
    ManiSkill

    ManiSkill

    SAPIEN Manipulation Skill Framework

    ManiSkill is a benchmark platform for training and evaluating reinforcement learning agents on dexterous manipulation tasks using physics-based simulations. Developed by Hao Su Lab, it focuses on robotic manipulation with diverse, high-quality 3D tasks designed to challenge perception, control, and planning in robotics. ManiSkill provides both low-level control and visual observation spaces for realistic learning scenarios.
    Downloads: 8 This Week
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  • 13
    nunif

    nunif

    Misc; latest version of waifu2x; 2D video to stereo 3D video

    nunif is a deep learning–based image processing framework focused on image upscaling, restoration, denoising, and enhancement tasks using neural network models. The project provides a collection of AI-powered utilities designed primarily for anime-style artwork, illustrations, and high-quality image restoration workflows. It includes command-line tools and graphical interfaces for applying trained neural models to improve image resolution and visual clarity while minimizing artifacts. nunif supports GPU acceleration and batch processing, making it suitable for creators, archivists, and enthusiasts handling large image collections. ...
    Downloads: 11 This Week
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  • 14
    DSPy

    DSPy

    DSPy: The framework for programming—not prompting—language models

    Developed by the Stanford NLP Group, DSPy (Declarative Self-improving Python) is a framework that enables developers to program language models through compositional Python code rather than relying solely on prompt engineering. It facilitates the construction of modular AI systems and provides algorithms for optimizing prompts and weights, enhancing the quality and reliability of language model outputs.
    Downloads: 9 This Week
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  • 15
    GLM-4.7

    GLM-4.7

    Advanced language and coding AI model

    GLM-4.7 is an advanced agent-oriented large language model designed as a high-performance coding and reasoning partner. It delivers significant gains over GLM-4.6 in multilingual agentic coding, terminal-based workflows, and real-world developer benchmarks such as SWE-bench and Terminal Bench 2.0. The model introduces stronger “thinking before acting” behavior, improving stability and accuracy in complex agent frameworks like Claude Code, Cline, and Roo Code. GLM-4.7 also advances “vibe...
    Downloads: 44 This Week
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  • 16
    Stable Diffusion WebUI Forge

    Stable Diffusion WebUI Forge

    Stable Diffusion WebUI Forge is a platform on top of Stable Diffusion

    ...It targets heavy users and researchers who push large models, control nets, and high-resolution pipelines where default settings can become bottlenecks. The fork typically introduces toggles for scheduler behavior, attention implementations, caching, and precision modes to reach better speed or quality on given hardware. It also focuses on stability during long sessions, aiming to reduce out-of-memory failures and provide clearer diagnostics when they occur. The UI surfaces advanced options in a way that remains recognizable to WebUI users, so migration costs are low while gaining experimental features. In practice, Forge serves as a proving ground for ideas that may later influence upstream tools, giving power users early access to cutting-edge techniques.
    Downloads: 1 This Week
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  • 17
    LTX-Video

    LTX-Video

    Official repository for LTX-Video

    LTX-Video is a sophisticated multimedia processing framework from Lightricks designed to handle high-quality video editing, compositing, and transformation tasks with performance and scalability. It provides runtime components that efficiently decode, encode, and manipulate video streams, frame buffers, and audio tracks while exposing a rich API for building customized editing features like transitions, effects, color grading, and keyframe automation.
    Downloads: 13 This Week
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  • 18
    DINOv3

    DINOv3

    Reference PyTorch implementation and models for DINOv3

    ...It continues the paradigm of learning strong image representations without labels using teacher–student distillation, but introduces a simplified and more scalable training recipe that performs well across datasets and architectures. DINOv3 removes the need for complex augmentations or momentum encoders, streamlining the pipeline while maintaining or improving feature quality. The model supports multiple backbone architectures, including Vision Transformers (ViT), and can handle larger image resolutions with improved stability during training. The learned embeddings generalize robustly across tasks like classification, retrieval, and segmentation without fine-tuning, showing state-of-the-art transfer performance among self-supervised models.
    Downloads: 13 This Week
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  • 19
    Guidance

    Guidance

    A guidance language for controlling large language models

    Guidance is an efficient programming paradigm for steering language models. With Guidance, you can control how output is structured and get high-quality output for your use case—while reducing latency and cost vs. conventional prompting or fine-tuning. It allows users to constrain generation (e.g. with regex and CFGs) as well as to interleave control (conditionals, loops, tool use) and generation seamlessly.
    Downloads: 5 This Week
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  • 20
    Uncertainty Baselines

    Uncertainty Baselines

    High-quality implementations of standard and SOTA methods

    Uncertainty Baselines is a collection of strong, well-documented training pipelines that make it straightforward to evaluate predictive uncertainty in modern machine learning models. Rather than offering toy scripts, it provides end-to-end recipes—data input, model architectures, training loops, evaluation metrics, and logging—so results are comparable across runs and research groups. The library spans canonical modalities and tasks, from image classification and NLP to tabular problems,...
    Downloads: 0 This Week
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  • 21
    pytype

    pytype

    A static type analyzer for Python code

    ...The tool consumes stub files (.pyi) for the standard library and third-party packages (from typeshed and its own built-ins), enabling accurate checks even in large, mixed-quality codebases. Developers can run pytype locally or wire it into CI to prevent regressions and track tightening type discipline over time. Because pytype infers types, it’s useful during gradual typing, surfacing mismatches, missing attributes, or unsafe unions before runtime. Documentation and a user guide detail configuration, supported features, and how inference interacts with modern Python idioms.
    Downloads: 0 This Week
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  • 22
    Step1X-3D

    Step1X-3D

    High-Fidelity and Controllable Generation of Textured 3D Assets

    ...The result is fully 3D assets — meshes + textures — which can be rendered from any viewpoint, textured consistently, and used in 3D applications. To achieve this, the project includes a massive curated dataset: among more than 5 million candidate 3D assets, it filters and standardizes to produce a high-quality 2 million–asset subset suitable for training.
    Downloads: 2 This Week
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  • 23
    DataProfiler

    DataProfiler

    Extract schema, statistics and entities from datasets

    DataProfiler is an AI-powered tool for automatic data analysis and profiling, designed to detect patterns, anomalies, and schema inconsistencies in structured and unstructured datasets. The DataProfiler is a Python library designed to make data analysis, monitoring, and sensitive data detection easy. Loading Data with a single command, the library automatically formats & loads files into a DataFrame. Profiling the Data, the library identifies the schema, statistics, entities (PII / NPI), and...
    Downloads: 6 This Week
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  • 24
    Fish Speech

    Fish Speech

    SOTA Open Source TTS

    Fish Speech is a state-of-the-art open-source text-to-speech project that has evolved into the OpenAudio series of advanced TTS models. The repository hosts the code and tooling for training, fine-tuning, and serving high-quality TTS, while the current flagship models (OpenAudio-S1 and S1-mini) are distributed via Fish Audio’s playground and Hugging Face. The models are evaluated with Seed TTS metrics and achieve exceptionally low word and character error rates, indicating strong intelligibility and alignment between text and audio. Fish Speech emphasizes expressive and controllable voices: it supports a long list of emotion tags, tone markers, and special audio effect markers that can be embedded in the text to drive prosody and vocal style, from basic emotions to nuanced states like sarcastic, conciliative, or hysterical. ...
    Downloads: 31 This Week
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  • 25
    SAM 3

    SAM 3

    Code for running inference and finetuning with SAM 3 model

    SAM 3 (Segment Anything Model 3) is a unified foundation model for promptable segmentation in both images and videos, capable of detecting, segmenting, and tracking objects. It accepts both text prompts (open-vocabulary concepts like “red car” or “goalkeeper in white”) and visual prompts (points, boxes, masks) and returns high-quality masks, boxes, and scores for the requested concepts. Compared with SAM 2, SAM 3 introduces the ability to exhaustively segment all instances of an open-vocabulary concept specified by a short phrase or exemplars, scaling to a vastly larger set of categories than traditional closed-set models. This capability is grounded in a new data engine that automatically annotated over four million unique concepts, producing a massive open-vocabulary segmentation dataset and enabling the model to achieve 75–80% of human performance on the SA-CO benchmark, which itself spans 270K unique concepts.
    Downloads: 20 This Week
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