Showing 2640 open source projects for "i86bi-linux-l3-adventerprisek..."

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  • 1
    Label Sleuth

    Label Sleuth

    Open source no-code system for text annotation and building of text

    An open-source no-code system for text annotation and building text classifiers. No AI knowledge needed. From task definition to working model in just a few hours! While domain experts label their data, Label Sleuth automatically trains in the background-appropriate machine learning models. To avoid wasted labeling effort, Label Sleuth employs active learning techniques to guide the user in what they should be labeled next. Domain experts can quickly start labeling their data through an...
    Downloads: 7 This Week
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  • 2
    Paper2GUI

    Paper2GUI

    Convert AI papers to GUI

    ...It already supports 40+ AI models, covering AI painting, speech synthesis, video frame complementing, video super-resolution, object detection, and image stylization. , OCR recognition and other fields. Support Windows, Mac, Linux systems. Paper2GUI: 一款面向普通人的 AI 桌面 APP 工具箱,免安装即开即用,已支持 40+AI 模型,内容涵盖 AI 绘画、语音合成、视频补帧、视频超分、目标检测、图片风格化、OCR 识别等领域。支持 Windows、Mac、Linux 系统。
    Downloads: 5 This Week
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  • 3
    PaddleX

    PaddleX

    PaddlePaddle End-to-End Development Toolkit

    PaddleX is a deep learning full-process development tool based on the core framework, development kit, and tool components of Paddle. It has three characteristics opening up the whole process, integrating industrial practice, and being easy to use and integrate. Image classification and labeling is the most basic and simplest labeling task. Users only need to put pictures belonging to the same category in the same folder. When the model is trained, we need to divide the training set, the...
    Downloads: 7 This Week
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  • 4
    OpenCLIP

    OpenCLIP

    An open source implementation of CLIP

    The goal of this repository is to enable training models with contrastive image-text supervision and to investigate their properties such as robustness to distribution shift. Our starting point is an implementation of CLIP that matches the accuracy of the original CLIP models when trained on the same dataset. Specifically, a ResNet-50 model trained with our codebase on OpenAI's 15 million image subset of YFCC achieves 32.7% top-1 accuracy on ImageNet. OpenAI's CLIP model reaches 31.3% when...
    Downloads: 7 This Week
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  • 5
    PyTorch Forecasting

    PyTorch Forecasting

    Time series forecasting with PyTorch

    PyTorch Forecasting aims to ease state-of-the-art time series forecasting with neural networks for both real-world cases and research alike. The goal is to provide a high-level API with maximum flexibility for professionals and reasonable defaults for beginners. A time series dataset class that abstracts handling variable transformations, missing values, randomized subsampling, multiple history lengths, etc. A base model class that provides basic training of time series models along with...
    Downloads: 7 This Week
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  • 6
    VibeVoice ComfyUI

    VibeVoice ComfyUI

    ComfyUI integration for Microsoft's VibeVoice text-to-speech model

    VibeVoice ComfyUI is a comprehensive wrapper that integrates Microsoft’s VibeVoice text-to-speech models directly into ComfyUI workflows. It exposes VibeVoice as a set of custom nodes so you can build single-speaker and multi-speaker voice generation pipelines visually, combining TTS with other audio or generative components. The integration supports high-quality single-speaker synthesis as well as scripted multi-speaker conversations, with optional voice cloning from audio samples for each...
    Downloads: 8 This Week
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  • 7
    Agent Framework

    Agent Framework

    Framework for building, orchestrating, and deploying AI agents

    Microsoft Agent Framework is an open source framework designed to help developers build, orchestrate, and deploy AI agents and multi-agent systems. It provides a unified programming model that supports both Python and .NET implementations, allowing developers to create agent-driven applications in multiple programming environments. It includes tools and abstractions for constructing simple conversational agents as well as complex workflows where multiple agents collaborate to complete tasks....
    Downloads: 7 This Week
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  • 8
    Gitingest

    Gitingest

    Create prompt-friendly codebase digests from any Git repository URL

    Gitingest is a developer utility that converts an entire Git repository into a structured, prompt-friendly text digest suitable for use with large language models. It analyzes a repository and produces a consolidated textual representation that includes the file structure and code content in an organized format. This makes it easier to provide meaningful code context when working with AI systems that require compact, readable inputs. Developers can generate these digests from either a local...
    Downloads: 7 This Week
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  • 9
    SGR Agent Core

    SGR Agent Core

    Schema-Guided Reasoning (SGR) has agentic system design

    SGR Agent Core is an open-source framework for building intelligent AI research agents based on a methodology known as Schema-Guided Reasoning (SGR). The framework provides a core library that allows developers to design autonomous agents capable of structured reasoning and complex task execution. Instead of relying solely on free-form prompts, the system organizes reasoning processes around schemas that guide how agents analyze problems, gather information, and generate outputs. This...
    Downloads: 7 This Week
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  • 10
    Chitu

    Chitu

    High-performance inference framework for large language models

    Chitu is a high-performance inference engine designed to deploy and run large language models efficiently in production environments. The framework focuses on improving efficiency, flexibility, and scalability for organizations that need to run LLM inference workloads across different hardware platforms. It supports heterogeneous computing environments, including CPUs, GPUs, and various specialized AI accelerators, allowing models to run across a wide range of infrastructure configurations....
    Downloads: 7 This Week
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  • 11
    bitsandbytes

    bitsandbytes

    Accessible large language models via k-bit quantization for PyTorch

    bitsandbytes is an open-source library designed to make training and inference of large neural networks more efficient by dramatically reducing memory usage. Built primarily for the PyTorch ecosystem, the library introduces advanced quantization techniques that allow models to operate using reduced numerical precision while maintaining high accuracy. These optimizations enable large language models and other deep learning architectures to run on hardware with limited memory resources,...
    Downloads: 7 This Week
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  • 12
    Claude Scientific Skills

    Claude Scientific Skills

    A set of ready to use Agent Skills for research, science, engineering

    Claude Scientific Skills is a large open source collection of ready-to-use scientific capabilities that extend AI coding agents into full research assistants. The project provides more than 170 curated skills covering domains such as genomics, drug discovery, medical imaging, physics, and advanced data analysis. Each skill bundles documentation, examples, and tool integrations so agents can reliably execute complex multi-step scientific workflows. The framework follows the open Agent Skills...
    Downloads: 7 This Week
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  • 13
    Unstract

    Unstract

    No-code LLM Platform to launch APIs and ETL Pipelines

    Unstract is a powerful open-source, no-code platform built to automate the extraction and structuring of unstructured documents using large language models and flexible workflows, enabling developers and data teams to turn messy files into organized JSON content without complex coding. It integrates a visual Prompt Studio environment where users can iteratively design extraction schemas, compare outputs from different models, and monitor costs and accuracy side by side, making it easier to...
    Downloads: 7 This Week
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  • 14
    Granite TSFM

    Granite TSFM

    Foundation Models for Time Series

    granite-tsfm collects public notebooks, utilities, and serving components for IBM’s Time Series Foundation Models (TSFM), giving practitioners a practical path from data prep to inference for forecasting and anomaly-detection use cases. The repository focuses on end-to-end workflows: loading data, building datasets, fine-tuning forecasters, running evaluations, and serving models. It documents the currently supported Python versions and points users to where the core TSFM models are hosted...
    Downloads: 7 This Week
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  • 15
    ContextForge MCP Gateway

    ContextForge MCP Gateway

    A Model Context Protocol (MCP) Gateway & Registry

    MCP Context Forge is a feature-rich gateway and registry that federates Model Context Protocol (MCP) servers and traditional REST services behind a single, governed endpoint. It exposes an MCP-compliant interface to clients while handling discovery, authentication, rate limiting, retries, and observability on the server side. The gateway scales horizontally, supports multi-cluster deployments on Kubernetes, and uses Redis for federation and caching across instances. Operators can define...
    Downloads: 7 This Week
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  • 16
    Open Interface

    Open Interface

    Control Any Computer Using LLMs

    Open Interface is a cross-platform application that allows users to control their computers using large language models (LLMs). By sending user requests to an LLM backend, it determines the necessary steps and executes them by simulating keyboard and mouse inputs. The system can adjust its actions based on real-time feedback, providing a self-driving computer experience.
    Downloads: 5 This Week
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  • 17
    SLM Lab

    SLM Lab

    Modular Deep Reinforcement Learning framework in PyTorch

    SLM Lab is a modular and extensible deep reinforcement learning framework designed for research and practical applications. It provides implementations of various state-of-the-art RL algorithms and emphasizes reproducibility, scalability, and detailed experiment tracking. SLM Lab is structured around a flexible experiment management system, allowing users to define, run, and analyze RL experiments efficiently.
    Downloads: 6 This Week
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  • 18
    AgentRun

    AgentRun

    The easiest, and fastest way to run AI-generated Python code safely

    AgentRun is a framework for building autonomous AI agents capable of executing complex tasks with minimal human intervention. It provides a structured environment for defining agent behaviors, managing workflows, and integrating AI models to achieve specific goals.
    Downloads: 6 This Week
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  • 19
    Shapash

    Shapash

    Explainability and Interpretability to Develop Reliable ML models

    Shapash is a Python library dedicated to the interpretability of Data Science models. It provides several types of visualization that display explicit labels that everyone can understand. Data Scientists can more easily understand their models, share their results and easily document their projects in an HTML report. End users can understand the suggestion proposed by a model using a summary of the most influential criteria.
    Downloads: 6 This Week
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  • 20
    Lazy Predict

    Lazy Predict

    Lazy Predict help build a lot of basic models without much code

    Lazy Predict helps build a lot of basic models without much code and helps understand which models work better without any parameter tuning.
    Downloads: 5 This Week
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  • 21
    Nerfstudio

    Nerfstudio

    A collaboration friendly studio for NeRFs

    Nerfstudio provides a simple API that allows for a simplified end-to-end process of creating, training, and testing NeRFs. The library supports a more interpretable implementation of NeRFs by modularizing each component. With more modular NeRFs, we hope to create a more user-friendly experience in exploring the technology. This is a contributor-friendly repo with the goal of building a community where users can more easily build upon each other’s contributions. Nerfstudio initially launched...
    Downloads: 7 This Week
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  • 22
    Argilla

    Argilla

    The open-source data curation platform for LLMs

    Argilla is a production-ready framework for building and improving datasets for NLP projects. Deploy your own Argilla Server on Spaces with a few clicks. Use embeddings to find the most similar records with the UI. This feature uses vector search combined with traditional search (keyword and filter based). Argilla is free, open-source, and 100% compatible with major NLP libraries (Hugging Face transformers, spaCy, Stanford Stanza, Flair, etc.). In fact, you can use and combine your preferred...
    Downloads: 7 This Week
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  • 23
    Marvin

    Marvin

    A batteries-included library for building AI-powered software

    Meet Marvin: a batteries-included library for building AI-powered software. Marvin's job is to integrate AI directly into your codebase by making it look and feel like any other function. Marvin introduces a new concept called AI Functions. These functions differ from conventional ones in that they don’t rely on source code, but instead generate their outputs on-demand through AI. With AI functions, you don't have to write complex code for tasks like extracting entities from web pages,...
    Downloads: 7 This Week
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  • 24
    TorchIO

    TorchIO

    Medical imaging toolkit for deep learning

    TorchIO is an open-source Python library for efficient loading, preprocessing, augmentation and patch-based sampling of 3D medical images in deep learning, following the design of PyTorch. It includes multiple intensity and spatial transforms for data augmentation and preprocessing. These transforms include typical computer vision operations such as random affine transformations and also domain-specific ones such as simulation of intensity artifacts due to MRI magnetic field inhomogeneity...
    Downloads: 7 This Week
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  • 25
    DeepLabCut

    DeepLabCut

    Implementation of DeepLabCut

    DeepLabCut™ is an efficient method for 2D and 3D markerless pose estimation based on transfer learning with deep neural networks that achieves excellent results (i.e. you can match human labeling accuracy) with minimal training data (typically 50-200 frames). We demonstrate the versatility of this framework by tracking various body parts in multiple species across a broad collection of behaviors. The package is open source, fast, robust, and can be used to compute 3D pose estimates or for...
    Downloads: 7 This Week
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