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Showing 85 open source projects for "result"
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Engram
A New Axis of Sparsity for Large Language Models
Engram is a high-performance embedding and similarity search library focused on making retrieval-augmented workflows efficient, scalable, and easy to adopt by developers building search, recommendation, or semantic matching systems. It provides utilities to generate embeddings from text or other structured data, index them using efficient approximate nearest neighbor algorithms, and perform real-time similarity queries even on large corpora. Engineered with speed and memory efficiency in... -
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Deep Research
Use any LLMs (Large Language Models) for Deep Research
...A simple web UI lets you enter topics and configure models, while the backend streams progress as sources are fetched and arguments are weighed. It offers MCP server support and SSE APIs, so IDEs and agent clients can drive the same workflow programmatically. The result is a repeatable process for scoping questions, collecting evidence, and producing a concise report with citations and reasoning steps. -
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Spark NLP
State of the Art Natural Language Processing
...Spark ML provides a set of machine learning applications that can be built using two main components, estimators and transformers. The estimators have a method that secures and trains a piece of data to such an application. The transformer is generally the result of a fitting process and applies changes to the target dataset. These components have been embedded to be applicable to Spark NLP. Pipelines are a mechanism for combining multiple estimators and transformers in a single workflow. They allow multiple chained transformations along a machine-learning task. -
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Step-Video-T2V
State-of-the-art (SoTA) text-to-video pre-trained model
...Its training and generation pipeline includes techniques like flow-matching, full 3D attention for temporal consistency, and fine-tuning approaches (e.g. video-based DPO) to improve fidelity and reduce artifacts. As a result, Step-Video-T2V aims to push the frontier of open-source video generation. -
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draw-a-ui
Draw wireframe sketches and generate HTML with AI vision models
...When a user sketches a UI on the canvas, the application captures the current drawing as SVG, converts it into a PNG image, and sends that image to a vision model that generates the corresponding markup. The result is an automated design-to-code workflow where rough interface ideas can quickly become functional web layouts. It is implemented as a modern web application built with Next.js and TypeScript and requires a compatible Node.js runtime to run locally. It is designed primarily as a demonstration of AI-assisted UI generation rather than a production-ready platform. -
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CAG
Cache-Augmented Generation: A Simple, Efficient Alternative to RAG
...This strategy allows the model to generate responses using the cached context directly, eliminating the need for repeated retrieval operations during runtime. As a result, the approach can significantly reduce latency and simplify system architecture compared with traditional RAG pipelines. The framework is particularly effective when the knowledge base is limited enough to fit within the extended context window of modern language models. -
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PowerInfer
High-speed Large Language Model Serving for Local Deployment
...PowerInfer incorporates specialized algorithms and sparse operators to manage neuron activation patterns and minimize data transfers between hardware components. As a result, it enables powerful language models to run on consumer hardware while achieving performance comparable to more expensive server-grade systems. -
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WorkAny
Desktop Agent for Any Task
...Powered by a combination of Claude Code as the primary runtime agent and a sandbox execution environment for safety, WorkAny integrates an agent SDK, MCP (Model Context Protocol) support, and custom skills to handle diverse tasks with contextual understanding. Users can connect multiple model providers, including OpenAI, OpenRouter, or custom endpoints, and WorkAny supports parallel task execution with asynchronous result viewing, enhancing productivity. -
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LMCache
Supercharge Your LLM with the Fastest KV Cache Layer
...These capabilities aim to lower latency, cut GPU cycles, and stabilize performance for production workloads with overlapping prompts or retrieval-augmented contexts. The end result is a cache fabric for LLMs that complements engines rather than replacing them. -
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GoCV
Go package for computer vision using OpenCV 4 and beyond
...CV software typically processes video images, then uses the data to extract information in order to do something useful. Since memory allocations for images in GoCV are done through C based code, the go garbage collector will not clean all resources associated with a Mat. As a result, any Mat created must be closed to avoid memory leaks. -
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LLaMA-Mesh
Unifying 3D Mesh Generation with Language Models
...The project includes a supervised fine-tuning dataset composed of interleaved text and mesh data, allowing the model to learn relationships between textual descriptions and 3D structures. As a result, the model can generate mesh models directly from text prompts, explain mesh structures in natural language, or output mixed text-and-mesh sequences. This unified representation enables a single model to operate across both textual and spatial domains. -
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Universal Commerce Protocol (UCP)
The common language for platforms, agents and businesses.
...Its modular, capability-based architecture allows businesses to expose only what they support while remaining flexible and extensible. By leveraging existing industry standards for payments, identity, and security, UCP avoids reinventing the wheel while ensuring reliability and trust. The result is a developer-friendly, future-ready protocol that simplifies commerce integration at global scale. -
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VibeThinker
Diversity-driven optimization and large-model reasoning ability
...The innovation lies in its training methodology: the team uses what they call the Spectrum-to-Signal Principle (SSP), where a first stage emphasizes diversity of reasoning paths (the “spectrum” phase) and a second stage uses reinforcement techniques (the “signal” phase) to refine toward correctness and strong reasoning. The result is a model that outpaces many much larger models on domain-specific benchmarks, demonstrating that smaller models, if trained carefully and with the right objectives, can achieve high performance in reasoning-centric tasks. -
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Step1X-3D
High-Fidelity and Controllable Generation of Textured 3D Assets
...TSDF surface), and a texture synthesis stage that conditions on geometry and optionally reference input (or prompts) to produce view-consistent textures using a diffusion-based texture module. 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. -
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Lightweight' GAN
Implementation of 'lightweight' GAN, proposed in ICLR 2021
Implementation of 'lightweight' GAN proposed in ICLR 2021, in Pytorch. The main contribution of the paper is a skip-layer excitation in the generator, paired with autoencoding self-supervised learning in the discriminator. Quoting the one-line summary "converge on single gpu with few hours' training, on 1024 resolution sub-hundred images". Augmentation is essential for Lightweight GAN to work effectively in a low data setting. You can test and see how your images will be augmented before... -
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PaSa
An advanced paper search agent powered by large language models
PaSa is an open-source “paper search agent” built around large language models (LLMs), designed to automate the process of academic literature retrieval with human-like decision making. Instead of simply translating a query into keywords and returning a flat list of matching papers, PaSa uses a dual-agent architecture (Crawler + Selector) that can iteratively search, read, analyze, and filter academic publications — simulating how a researcher might dig through citation networks, expand... -
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General Knowledge Machine Project
Intellect Modeling Kit: assisting research, diagnostics, consulting
We humans are bound by intellectual abilities. All knowledge is far beyond power of any person. The only way to apply knowledge is to build machines able to present it human way but not limited by volume. Intellect Modeling Kit (IMK) is intended to build knowledge machines (KM) assisting experts on the steps of activity: * Observation; * Producing propositions based on knowledge; * Elimination of impossible propositions; * Selection and verification of the most appropriate... -
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SpeakLogPSU can speak chat messages with an individual voice if the NPC or player was configured or with a default one. You will never miss if someone talks to you. Voice cloning can be accomplished with Coqui in less than five minutes without GPU. The result is archived and can be used the next time in game. Some TTS projects already started to add tag support to speak text with emotions or sing it. If a game designer has that in mind with a good chat log she can voiced her game over night. reads the log and sends new chat text to piper. ~/.config/Epic/PSUnreal/Saved/Logs/Pongo_Donjo_chat.txt If a line number is set it can speak all the chat text and waits for new chat text. ...
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Style Aligned
Official code for Style Aligned Image Generation via Shared Attention
...Instead of fully re-generating an image—and risking changes to lighting, texture, or rendering choices—the method aligns internal features across denoising steps so the target edit inherits the source style. This alignment acts like a constraint on the model’s evolution, steering composition, palette, and brushwork even as objects or attributes change. The result is more consistent edits across a set, which is crucial for workflows like product variations, character sheets, or brand-coherent art. The repository provides reproducible scripts, reference prompts, and guidance for tuning strengths so users can dial in subtle retouches or bolder substitutions. Because it builds on widely used diffusion checkpoints, creators can integrate it without training or dataset collection. -
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fastquant
Backtest and optimize your ML trading strategies with only 3 lines
...The framework enables users to test common strategies such as moving average crossovers, momentum trading, and custom indicators on historical stock data. By automating data retrieval, strategy evaluation, and result visualization, the library reduces the barrier to entry for individuals interested in quantitative finance. The project also supports optimization workflows that allow users to search for parameter combinations that improve trading strategy performance. -
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Promptify
se GPT or other prompt based models to get structured output
Promptify is an open-source Python library designed to simplify prompt engineering and the development of natural language processing pipelines using large language models. The project provides tools that help developers generate structured prompts for different NLP tasks and apply them across multiple generative AI systems. Instead of manually crafting prompts for each task, Promptify introduces a unified architecture that combines prompt templates, language model interfaces, and processing... -
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TXM
Unicode XML TEI text analysis platform
TXM is a free and open-source cross-platform Unicode & XML based text analysis environment and graphical client, supporting Windows, Linux and Mac OS X. It can also be used online as a J2EE standard compliant web portal (GWT based) with access control built in. DOWNLOAD LATEST VERSION OF TXM : http://textometrie.ens-lyon.fr/spip.php?rubrique61&lang=en TXM offers a comprehensive range of analysis tools (concordances, collocate search, frequency lists, etc.) based on the powerfull CQP... -
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Translation of Selected text or Clipboard contents powered by Google. HotKeys Paste/Change Text auto translated. View in Balloon/Window the result of translation, besides being sent to the clipboard. Screen Capture of Desktop/Game > OCR > Translated.
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ChatGPT Advanced
Browser extension adding web search results to ChatGPT prompts easily
chatgpt-advanced, commonly known as WebChatGPT, is an open source browser extension designed to enhance the capabilities of ChatGPT by integrating real-time web search results into user prompts. It works by intercepting queries submitted to the ChatGPT interface and optionally augmenting them with information gathered from search engines before sending the prompt to the chatbot. This approach allows the model to generate responses that are more current and contextually relevant compared to... -
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ConvNeXt V2
Code release for ConvNeXt V2 model
...The V2 version introduces a fully convolutional masked autoencoder (FCMAE) framework where parts of the image are masked and the network reconstructs the missing content, marrying convolutional inductive bias with powerful pretraining. A key innovation is a new Global Response Normalization (GRN) layer added to the ConvNeXt backbone, which enhances feature competition across channels. The result is a convnet that competes strongly with transformer architectures on recognition benchmarks while being efficient and hardware-friendly. The repository provides official PyTorch implementations for multiple model sizes (Atto, Femto, Pico, up through Huge), conversion from JAX weights, code for pretraining/fine-tuning, and pretrained checkpoints. ...
