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Showing 84 open source projects for "less"
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Weights and Biases
Tool for visualizing and tracking your machine learning experiments
...Track and visualize all the pieces of your machine learning pipeline, from datasets to production models. Quickly identify model regressions. Use W&B to visualize results in real time, all in a central dashboard. Focus on the interesting ML. Spend less time manually tracking results in spreadsheets and text files. Capture dataset versions with W&B Artifacts to identify how changing data affects your resulting models. Reproduce any model, with saved code, hyperparameters, launch commands, input data, and resulting model weights. Set wandb.config once at the beginning of your script to save your hyperparameters, input settings (like dataset name or model type), and any other independent variables for your experiments. ... -
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Depth Pro
Sharp Monocular Metric Depth in Less Than a Second
Depth Pro is a foundation model for zero-shot metric monocular depth estimation, producing sharp, high-frequency depth maps with absolute scale from a single image. Unlike many prior approaches, it does not require camera intrinsics or extra metadata, yet still outputs metric depth suitable for downstream 3D tasks. Apple highlights both accuracy and speed: the model can synthesize a ~2.25-megapixel depth map in around 0.3 seconds on a standard GPU, enabling near real-time applications. The... -
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UltraRAG
Less Code, Lower Barrier, Faster Deployment
UltraRAG 2.0 is a low-code, MCP-enabled RAG framework that aims to lower the barrier to building complex retrieval pipelines for research and production. It provides end-to-end recipes—from encoding and indexing corpora to deploying retrievers and LLMs—so users can reproduce baselines and iterate rapidly. The toolkit comes with built-in support for popular RAG datasets, large corpora, and canonical baselines, plus documentation that walks from “quick start” to debugging and case analysis. It... -
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Stop Slop
A skill file for removing AI tells from prose
...The skill is useful for drafting, editing, polishing, and quality-checking prose before publication. Its main value is giving writers and AI assistants a practical checklist for making text feel less synthetic and more intentional. -
Train ML Models With SQL You Already KnowBuild and deploy ML models using familiar SQL. Automate data prep with built-in Gemini. Query 1 TB and store 10 GB free monthly.
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PowerInfer
High-speed Large Language Model Serving for Local Deployment
...Its architecture exploits the observation that only a subset of neurons in large models are frequently activated, allowing the system to preload frequently used neurons into GPU memory while processing less common activations on the CPU. This hybrid execution strategy significantly reduces memory bottlenecks and improves overall inference speed. 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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Modelence
Modelence is an all-in-one TypeScript platform
Modelence is an all-in-one TypeScript platform aimed at helping teams ship production web apps with far less boilerplate than a typical full-stack setup. It positions itself as a Supabase-style experience tailored toward MongoDB-centric development, bundling common backend needs like authentication, database integration, and observability into a cohesive framework. The project is built to support modern application workflows where product teams want to move quickly without stitching together many separate services and libraries. ... -
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Avalanche
End-to-End Library for Continual Learning based on PyTorch
Avalanche is an end-to-end Continual Learning library based on Pytorch, born within ContinualAI with the unique goal of providing a shared and collaborative open-source (MIT licensed) codebase for fast prototyping, training and reproducible evaluation of continual learning algorithms. Avalanche can help Continual Learning researchers in several ways. This module maintains a uniform API for data handling: mostly generating a stream of data from one or more datasets. It contains all the major... -
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Rubix ML
A high-level machine learning and deep learning library for PHP
...In addition, we provide tutorials and other educational content to help you get started using ML in your projects. Our intuitive interface is quick to grasp while hiding alot of power and complexity. Write less code and iterate faster leaving the hard stuff to us. Rubix ML utilizes a versatile modular architecture that is defined by a few key abstractions and their types and interfaces. Train models in a fraction of the time by installing the optional Tensor extension powered by C. Learners such as neural networks will automatically get a performance boost. -
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ChatOllama
ChatOllama is an open-source AI chatbot
...Deployment is streamlined with Docker Compose, and the project also includes internationalization and modular feature toggles for controlling what parts of the system are enabled. As a result, ChatOllama feels less like a single chatbot and more like a flexible self-hosted AI workspace. -
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SageAttention
NeurIPS2025 Spotlight] Quantized Attention
...The system achieves this by using low-precision numerical formats such as INT4, FP8, or INT8 to represent key matrices within the attention computation. These optimizations allow models to perform matrix operations faster and consume less memory during inference. SageAttention is designed to function as a plug-and-play replacement for standard attention implementations, enabling developers to accelerate existing models without modifying their architecture. -
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Hugging Face Skills
Definitions for AI/ML tasks like dataset creation
...By formalizing best practices and workflows, Skills helps transform general-purpose coding agents into domain-aware assistants that can execute complex ML pipelines with less manual prompting. The repository also includes ready-to-use skills for common Hugging Face operations and encourages teams to extend them with custom domain logic. -
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Context Engineering Template
Context engineering is the new vibe coding
...Instead of relying solely on short prompts, this project encourages developers to create rich, structured context files that include project rules, examples, and validation criteria so that AI systems can act more like informed collaborators and less like general-purpose generators. The repository provides templates such as CLAUDE.md for defining global project rules, INITIAL.md for feature requests, and folders for examples, PRPs, validation scripts, and settings to support systematic prompt generation and execution with tools like Claude Code. By using this template, teams can ensure consistency across AI outputs, reduce errors that stem from contextual misunderstandings, and build reusable patterns. -
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Qwen2.5-Math
A series of math-specific large language models of our Qwen2 series
Qwen2.5-Math is a series of mathematics-specialized large language models in the Qwen2 family, released by Alibaba’s QwenLM. It includes base models (1.5B / 7B / 72B parameters), instruction-tuned versions, and a reward model (RM) to improve alignment. Unlike its predecessor Qwen2-Math, Qwen2.5-Math supports both Chain-of-Thought (CoT) reasoning and Tool-Integrated Reasoning (TIR) for solving math problems, and works in both Chinese and English. It is optimized for solving mathematical... -
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DotVVM
Open source MVVM framework for Web Apps
...Save your time with GridView, FileUpload and other components shipped with the framework. Don't spend the time building an API. Just load data from the database and use data-binding to display them. DotVVM needs less than 100 kB of JavaScript code. It's smaller than other ASP.NET-based frameworks. DotVVM offers a free Visual Studio extension giving you all the comfort you are used to. DotVVM comes with ready-made components you can use in your HTML files. The state and user interactions are handled in view models - C# classes. The controls render simple HTML which can be styled easily. ... -
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SoniTranslate
Synchronized Translation for Videos
...The project supports a wide range of languages for translation, spanning major world languages (English, Spanish, French, German, Chinese, Arabic, etc.) and many regional or less widely spoken languages, making it suitable for broad internationalization. It offers multiple usage modes, including a Colab notebook for cloud-based experimentation, a Hugging Face Space demo for quick trials, and instructions. -
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uweb browser: unlimited power
minimal suckless android web browser with unlimited power
... - Customizable: user-defined menus, (new) buttons and gestures for user agents, bookmarklets, url services, shell commands, internal functionality links and text processing etc. - Convenient: book/dictionary/txt/command line/app can be search engine. - Tiny: less than 200k - Fast: run fast, even with thousands of user provided css/scripts - Efficient: less touches, one click to reach any number of search engines without repeated input; automate online services. - URL bar command line support ("!" and .js files as commands). - user-defined site-specific JS/CSS/HTML/preprocessing. - Online play/preview/preprocess for downloadable resources... -
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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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Thinknowlogy
The world's only naturally intelligent knowledge technology
...This naturally occurring logic provides concrete clues for organizing natural objects, like: - Grouping objects that belong together, - Separating objects that don't belong together, - Archiving objects that have become less important. Natural language and spatial information are sources of natural intelligence: - Natural language is providing concrete logic for organizing knowledge objects, - Spatial information provides concrete logic for organizing spatial objects (utilized in, e.g., self-driving cars). In this way, our brains know how to organize their knowledge and spatial information. ... -
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VectorDB
A Python vector database you just need, no more, no less
vectordb is a Pythonic vector database offers a comprehensive suite of CRUD (Create, Read, Update, Delete) operations and robust scalability options, including sharding and replication. It's readily deployable in a variety of environments, from local to on-premise and cloud. vectordb delivers exactly what you need - no more, no less. It's a testament to effective Pythonic design without over-engineering, making it a lean yet powerful solution for all your needs. vectordb capitalizes on the powerful retrieval prowess of DocArray and the scalability, reliability, and serving capabilities of Jina. Here's the magic: DocArray serves as the engine driving vector search logic, while Jina guarantees efficient and scalable index serving. ... -
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OnnxStream
Lightweight inference library for ONNX files, written in C++
The challenge is to run Stable Diffusion 1.5, which includes a large transformer model with almost 1 billion parameters, on a Raspberry Pi Zero 2, which is a microcomputer with 512MB of RAM, without adding more swap space and without offloading intermediate results on disk. The recommended minimum RAM/VRAM for Stable Diffusion 1.5 is typically 8GB. Generally, major machine learning frameworks and libraries are focused on minimizing inference latency and/or maximizing throughput, all of which... -
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ChatLLM Web
Chat with LLM like Vicuna totally in your browser with WebGPU
...To use this app, you need a browser that supports WebGPU, such as Chrome 113 or Chrome Canary. Chrome versions ≤ 112 are not supported. You will need a GPU with about 6.4GB of memory. If your GPU has less memory, the app will still run, but the response time will be slower. The first time you use the app, you will need to download the model. For the Vicuna-7b model that we are currently using, the download size is about 4GB. After the initial download, the model will be loaded from the browser cache for faster usage. -
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PerlPP
Perl preprocessor - embed Perl source in any file
Translates Text+Perl to Text. It can be used for any kind of text templating, e.g. code generation. No external modules are required, just a single file. Requires Perl 5.10.1+. PerlPP runs in two passes: it generates a Perl script from your input, and then it runs the generated script. If you see error at (eval ##) (for some number ##), it means there was an error in the generated script. The -D switch defines elements of %D. If you do not specify a value, the value true (a constant in the... -
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Ultroid
Telegram UserBot, Built in Python Using Telethon lib
Ultroid, a pluggable telegram userbot, made in python using Telethon! Ultroid has been written from scratch, making it more stable and less crashes. Ultroid warns you when you try to install/execute dangerous stuff (people nowadays make plugins to hack user accounts, Ultroid is safe). Unlike many others userbots that are being suspended by Heroku, Ultroid doesn't get suspended. Ultroid has been written from scratch, making it more stable and less of crashes. Error handling been done in the best way possible, such that the bot doesn't crash and stop all of a sudden. ... -
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Fairseq
Facebook AI Research Sequence-to-Sequence Toolkit written in Python
Fairseq(-py) is a sequence modeling toolkit that allows researchers and developers to train custom models for translation, summarization, language modeling and other text generation tasks. We provide reference implementations of various sequence modeling papers. Recent work by Microsoft and Google has shown that data parallel training can be made significantly more efficient by sharding the model parameters and optimizer state across data parallel workers. These ideas are encapsulated in the... -
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NWT - Pytorch (wip)
Implementation of NWT, audio-to-video generation, in Pytorch
...The paper proposes a new discrete latent representation named Memcodes, which can be succinctly described as a type of multi-head hard-attention to learned memory (codebook) key/values. They claim the need for less codes and smaller codebook dimensions in order to achieve better reconstructions.
