Search Results for "balance"
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Showing 66 open source projects for "balance"
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Faster Whisper
Faster Whisper transcription with CTranslate2
...The system is particularly useful for real-time or large-scale transcription tasks where performance is critical. It supports multiple model sizes, allowing users to balance speed and accuracy based on their needs. The architecture is designed to run efficiently on both CPUs and GPUs, making it accessible across different environments. It also includes support for streaming and batch processing, enabling flexible deployment scenarios. Overall, faster-whisper makes state-of-the-art speech recognition more practical for production use cases by improving speed and efficiency without sacrificing quality. -
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OpenHands
Open-source autonomous AI software engineer
...So we're building all our agents in the open on GitHub, under the MIT license. Our agents can do anything a human developer can: they write code, run commands, and use the web. We're partnering with AI safety experts like Invariant Labs to balance innovation with security. -
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LLaMA 3
The official Meta Llama 3 GitHub site
This repository is the former home for Llama 3 model artifacts and getting-started code, covering pre-trained and instruction-tuned variants across multiple parameter sizes. It introduced the public packaging of weights, licenses, and quickstart examples that helped developers fine-tune or run the models locally and on common serving stacks. As the Llama stack evolved, Meta consolidated repositories and marked this one deprecated, pointing users to newer, centralized hubs for models,... -
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FramePack
Lets make video diffusion practical
FramePack explores compact representations for sequences of image frames, targeting tasks where many near-duplicate frames carry redundant information. The idea is to “pack” frames by detecting shared structure and storing differences efficiently, which can accelerate training or inference on video-like data. By reducing I/O and memory bandwidth, datasets become lighter to load while models still see the essential temporal variation. The repository demonstrates both packing and unpacking... -
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Bayesian Optimization
Python implementation of global optimization with gaussian processes
...Explore the options exemplifying the balance between exploration and exploitation and how to control it. Explore the domain reduction notebook to learn more about how search can be sped up by dynamically changing parameters' bounds. -
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ComfyUI SUPIR
SUPIR upscaling wrapper for ComfyUI
...The project leverages modern generative models to produce sharp, detailed outputs while preserving the original structure of the image. It can be combined with other ComfyUI nodes for tasks such as stylization or animation. The system is designed to balance quality and performance, making it suitable for both experimentation and production use. Overall, it brings state-of-the-art image enhancement capabilities into the ComfyUI ecosystem. -
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VOID
Video Object and Interaction Deletion
...Unlike traditional inpainting methods that only erase pixels or simple artifacts, VOID models the full interaction dynamics between objects and their environment, including shadows, reflections, and even physical consequences such as movement or balance changes. Built on top of transformer-based architectures and fine-tuned for video inpainting tasks, the system uses interaction-aware mask conditioning to ensure temporal consistency across frames. One of its most notable capabilities is its ability to simulate realistic scene behavior after object removal, such as causing an object to fall naturally if its support is removed, which significantly enhances realism. -
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TurboQuant PyTorch
From-scratch PyTorch implementation of Google's TurboQuant
...The project focuses on reducing the computational and memory footprint of models by converting floating-point representations into lower-precision formats while preserving performance. It provides tools for experimenting with different quantization strategies, enabling developers to balance accuracy and efficiency depending on their application. The framework integrates directly with PyTorch workflows, making it accessible for researchers and engineers already familiar with the ecosystem. It is particularly useful for deploying models in resource-constrained environments such as edge devices or real-time systems. -
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OpenMemory
Local long-term memory engine for AI apps with persistent storage
...OpenMemory is built around a hierarchical memory architecture that organizes data into semantic sectors and connects them through a graph-based structure for efficient retrieval. It supports multiple embedding strategies, including synthetic and semantic embeddings, allowing developers to balance speed and accuracy depending on their use case. OpenMemory integrates with various AI tools and environments, offering SDKs and APIs that simplify adding memory capabilities to applications. OpenMemory also includes features like memory decay, reinforcement, and temporal filtering to ensure relevant information remains prioritized while outdated data gradually loses importance. -
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screenshot-to-code
Drop in a screenshot and convert it to clean code
...The tool focuses on practical developer outputs—semantic markup, reusable components, and readable classes—so the result is a starting point you can refine, not a throwaway demo. It also supports multi-model backends and local-first options to balance cost, speed, and privacy. Teams use it for rapid prototyping, migrating static mockups to codebases, and exploring design alternatives without hand-coding every pixel from scratch. -
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...Yogstation prioritizes accessibility for new players while maintaining depth for veterans, making it one of the more popular SS13 community forks. The code and assets are open for contribution, allowing developers to propose fixes, features, and balance changes. With active updates, Yogstation continues to evolve as a distinctive branch of the SS13 ecosystem.
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OpenViking
Context database designed specifically for AI Agents
...It’s primarily designed to serve as a high-performance, scalable backend for storing app context, embeddings, conversational histories, and other textual artifacts that need rapid lookup and semantic search, which makes it especially useful for systems like chatbots or memory-augmented agents. The project is implemented with performance in mind, often leveraging optimized data structures that balance fast reads and writes with minimal resource consumption. Developers can integrate OpenViking into modern AI stacks to unify context storage across services, enabling consistent session history, personalized responses, and richer search experiences. -
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MiniRAG
Making RAG Simpler with Small and Open-Sourced Language Models
...Its minimal footprint makes it suitable for local research assistants, chatbots, help desks, or knowledge bases embedded in applications with limited resources. Despite its simplicity, it includes features such as chunking logic, configurable embedding models, and optional caching to balance performance and accuracy. -
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GT New Horizons Mod Pack
New Modpack with Gregtech, Thaumcraft and Witchery
You are looking at a big progressive kitchensink pack for Minecraft 1.7.10 balanced around the mod GregTech. Over 9 years of development (and still going) have formed a balance and refinement that only a handful of packs can keep up with. We are talking about thousands of recipe tweaks, a massive questbook with over 3000 quests, unique world generation, custom mods coded for the pack, custom Thaumonomicon pages, and many more. The main intentions of the pack are a long-lasting experience and tying mods together in a progressive fashion, making it feel more like a single game than a compilation of mods thrown together. ... -
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Writer Framework
No-code in the front, Python in the back. An open-source framework
Writer Framework is an open source platform designed to help developers build AI-powered applications by combining a visual interface builder with a Python-based backend architecture. It follows a hybrid approach where user interfaces are created using a drag-and-drop editor while business logic is implemented in Python, allowing teams to balance speed and flexibility without sacrificing control. The framework is particularly focused on AI use cases, enabling developers to integrate large language models, knowledge graphs, and custom machine learning workflows into user-facing applications. Its architecture enforces a clear separation of concerns between frontend and backend, which improves maintainability and scalability as applications grow in complexity. ... -
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BoxMOT
Pluggable SOTA multi-object tracking modules for segmentation
...It also includes evaluation tools and benchmarking pipelines that allow researchers to test tracking performance on standard datasets such as MOT17 and MOT20. The system offers different performance modes that balance computational efficiency with tracking accuracy depending on the application requirements. -
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Watermark Anything
Official implementation of Watermark Anything with Localized Messages
...Unlike traditional watermarking methods that rely on uniform embedding, WAM supports spatially localized watermarks, enabling targeted protection of specific image regions or objects. The model is trained to balance imperceptibility, ensuring minimal visual distortion, with robustness against transformations and edits such as cropping or motion. -
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Trafilatura
Python & command-line tool to gather text on the Web
...Going from raw HTML to essential parts can alleviate many problems related to text quality, first by avoiding the noise caused by recurring elements (headers, footers, links/blogroll etc.) and second by including information such as author and date in order to make sense of the data. The extractor tries to strike a balance between limiting noise (precision) and including all valid parts (recall). It also has to be robust and reasonably fast, it runs in production on millions of documents. -
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Dia
A TTS model capable of generating ultra-realistic dialogue
...Dia is released with pretrained checkpoints and inference code, with weights hosted on Hugging Face, so researchers and developers can quickly try it or integrate it into pipelines. The base model currently targets English and has around 1.6 billion parameters, offering a strong balance between realism and computational cost, while the ecosystem also includes Dia2. -
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Claw Compactor
14-stage Fusion Pipeline for LLM token compression
...It is especially useful in autonomous workflows where agents accumulate large volumes of interaction history over time. The project aligns with broader strategies in AI systems that balance memory retention with computational constraints. Overall, claw-compactor functions as an infrastructure component that enhances scalability and stability in persistent AI agent environments. -
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machine learning tutorials
machine learning tutorials (mainly in Python3)
...The repository integrates numerous popular machine learning frameworks and libraries such as scikit-learn, PyTorch, TensorFlow, XGBoost, and Hugging Face. It aims to strike a balance between theoretical explanation and practical coding by demonstrating algorithms both from scratch and using established libraries. The content is organized into multiple sections covering topics such as clustering, regression, dimensionality reduction, recommender systems, and model evaluation. -
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TerraGov Marine Corps
TGMC: TerraGov Marine Corps, a SS13 mod
...The project focuses heavily on teamwork, coordination, and immersive gameplay, providing players with different roles such as engineers, medics, or combat marines to ensure strategic variety. TGMC offers a persistent, evolving experience where community contributions shape mechanics, balance, and lore. The codebase serves as both a live game server foundation and a development platform for contributors who want to expand gameplay features, design new mechanics, or refine existing systems. With its mixture of roleplay, tactical combat, and science fiction setting, TGMC provides a distinctive twist on the SS13 lineage. -
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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... -
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GLM-V
GLM-4.5V and GLM-4.1V-Thinking: Towards Versatile Multimodal Reasoning
...GLM-4.5V builds on the flagship GLM-4.5-Air foundation (106B parameters, 12B active), achieving state-of-the-art results on 42 benchmarks across image, video, document, GUI, and grounding tasks. It introduces hybrid training for broad-spectrum reasoning and a Thinking Mode switch to balance speed and depth of reasoning. GLM-4.1V-9B-Thinking incorporates reinforcement learning with curriculum sampling (RLCS) and Chain-of-Thought reasoning, outperforming models much larger in scale (e.g., Qwen-2.5-VL-72B) across many benchmarks. -
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GLM-4.1V
GLM-4.6V/4.5V/4.1V-Thinking, towards versatile multimodal reasoning
GLM-4.1V — often referred to as a smaller / lighter version of the GLM-V family — offers a more resource-efficient option for users who want multimodal capabilities without requiring large compute resources. Though smaller in scale, GLM-4.1V maintains competitive performance, particularly impressive on many benchmarks for models of its size: in fact, on a number of multimodal reasoning and vision-language tasks it outperforms some much larger models from other families. It represents a...
