Search Results for "open project" - Page 15
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Showing 794 open source projects for "open project"
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WeClone
One-stop solution for creating your digital avatar from chat history
WeClone is an open source AI project designed to replicate a person’s conversational style and personality by training models on chat history data. The system analyzes message patterns, linguistic style, and contextual behavior in order to generate responses that resemble the original user’s communication style. It is intended primarily as an experimental exploration of digital personality modeling and conversational AI personalization. -
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OpenViking
Context database designed specifically for AI 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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SERA CLI
A tool to use the Ai2 Open Coding Agents Soft-Verified Agents
SERA CLI is a command-line tool created by AllenAI to enable developers to interact with the SERA (Soft-Verified Efficient Repository Agents) model family using Claude Code as the execution front end. It provides a convenient interface for deploying, testing, and using SERA models without needing to write scaffold code from scratch, acting as both a proxy and utility wrapper to simplify workflows that involve large agent models. Through sera-cli, users can connect to local or cloud-hosted... -
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DFlash
Block Diffusion for Ultra-Fast Speculative Decoding
DFlash is an open-source framework for ultra-fast speculative decoding using a lightweight block diffusion model to draft text in parallel with a target large language model, dramatically improving inference speed without sacrificing generation quality. It acts as a “drafter” that proposes likely continuations which the main model then verifies, enabling significant throughput gains compared to traditional autoregressive decoding methods that generate token by token. -
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Anthropic's Original Performance
Anthropic's original performance take-home, now open for you to try
Anthropic's Original Performance repository contains the publicly released version of a performance challenge originally used by Anthropic as part of their technical interview process, offering developers the opportunity to optimize and benchmark low-level code against simulated models. The project sets up a baseline performance problem where participants work to reduce simulated “clock cycles” required to run a given workload, effectively challenging them to engineer faster code under... -
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MiniMind-V
"Big Model" trains a visual multimodal VLM with 26M parameters
MiniMind-V is an experimental open-source project that aims to train a very small multimodal vision–language model (VLM) from scratch with extremely low compute and cost, making research and experimentation accessible to more people. The repository showcases training workflows and code designed to produce a 26-million parameter model—including both image and text capabilities—using minimal resources in very little time, reflecting a trend toward democratizing AI research. ... -
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NeuTTS Nano
On-device TTS model by Neuphonic
NeuTTS Nano is an open-source collection of on-device text-to-speech speech language models from Neuphonic. It is built for natural-sounding voice generation that can run locally instead of relying on a remote web API. The project emphasizes instant voice cloning, real-time performance, and deployment on smaller devices such as phones, laptops, and Raspberry Pi-class hardware. -
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MOSS-TTS Family
MOSS‑TTS Family open‑source speech and sound generation model
MOSS-TTS is an open-source speech and sound generation model family built for high-fidelity, expressive, and production-oriented audio workflows. It covers long-form speech, voice cloning, multi-speaker dialogue, voice design, environmental sound effects, and real-time streaming TTS. The project is designed for complex real-world use cases where a single speech model may not be enough. -
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Prometheus-Eval
Evaluate your LLM's response with Prometheus and GPT4
Prometheus-Eval is an open-source framework designed to evaluate the outputs of large language models using specialized evaluator models known as Prometheus. The project provides tools, datasets, and scripts that allow developers and researchers to measure the quality of LLM responses through automated scoring rather than relying solely on human evaluators. -
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RLHF-Reward-Modeling
Recipes to train reward model for RLHF
...It supports multiple optimization strategies commonly used in alignment pipelines, including reinforcement learning with PPO, iterative supervised fine-tuning using rejection sampling, and direct preference optimization methods. The project also includes evaluation results showing that the trained reward models can achieve competitive performance compared with other open-source alignment systems. -
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Index
The SOTA Open-Source Browser Agent
...The project is built to integrate easily with applications through a simple programming interface, allowing developers to embed browser automation capabilities directly into their software systems. Index can perform tasks such as navigating pages, filling forms, collecting data, and analyzing web content without requiring manual scripting for each website. -
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Skywork-R1V4
Skywork-R1V is an advanced multimodal AI model series
Skywork-R1V is an open-source multimodal reasoning model designed to extend the capabilities of large language models into vision-language tasks that require complex logical reasoning. The project introduces a model architecture that transfers the reasoning abilities of advanced text-based models into visual domains so the system can interpret images and perform multi-step reasoning about them. -
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The Alignment Handbook
Robust recipes to align language models with human and AI preferences
The Alignment Handbook is an open-source resource created to provide practical guidance for aligning large language models with human preferences and safety requirements. The project focuses on the post-training stage of model development, where models are refined after pre-training to behave more helpfully, safely, and reliably in real-world applications. It provides detailed training recipes that explain how to perform tasks such as supervised fine-tuning, preference modeling, and reinforcement learning from human feedback. ... -
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Agents 2.0
An Open-source Framework for Data-centric Language Agents
Agents is an open-source framework designed to build and train autonomous language agents through a data-centric and learning-oriented architecture. The project introduces a concept known as agent symbolic learning, which treats an agent pipeline similarly to a neural network computational graph. In this framework, each node in the pipeline represents a step in the reasoning or action process, while prompts and tools act as adjustable parameters analogous to neural network weights. ... -
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DeepSearcher
Open Source Deep Research Alternative to Reason and Search
DeepSearcher is an open-source “deep research” style system that combines retrieval with evaluation and reasoning to answer complex questions using private or enterprise data. It is designed around the idea that high-quality answers require more than top-k retrieval, so it orchestrates multi-step search, evidence collection, and synthesis into a comprehensive response. -
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LuxTTS
A high-quality rapid TTS voice cloning model
...The project supports zero-shot voice cloning, meaning it can adapt to a reference speaker’s voice with minimal example data, enabling realistic and personalized synthetic speech. Intended for developers, hobbyists, and creators, the repository includes installation instructions, usage examples, and Python APIs that make it feasible to integrate the model in local workflows, web demos, or production systems. -
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Dolphin
Document Image Parsing via Heterogeneous Anchor Prompting”
...Because multimedia delivery requirements vary widely (adaptive streaming, live feeds, cross-platform compatibility, custom UI, performance constraints), Dolphin aims to offer a foundation that developers can build upon or adapt to their needs. It is designed to integrate with other tools and libraries and provide stable playback or media-processing pipelines, while remaining open-source so that users can inspect, extend, and adapt it. -
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Generative AI for Beginners (Version 3)
21 Lessons, Get Started Building with Generative AI
...It also walks through modern application techniques such as function calling, RAG with vector databases, working with open source models, agents, fine-tuning, and using SLMs. Each lesson includes a short video, a written guide, runnable samples for Azure OpenAI, the GitHub Marketplace Model Catalog, and the OpenAI API, plus a “Keep Learning” section for deeper study. -
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USO
Open-sourced unified customization model
...By decoupling style and subject, USO enables reuse of learned style/style-embeddings across different subjects, or vice versa, which makes generation more modular and controllable. The project provides tooling (in Python) including inference and workflow scripts, example configurations, and support for generation pipelines; and as of 2025, USO is also natively supported in some mainstream generative-art UI pipelines (e.g. ComfyUI) to ease adoption. -
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Perception Models
State-of-the-art Image & Video CLIP, Multimodal Large Language Models
...Meanwhile, PLM integrates with PE to power vision-language modeling, achieving results competitive with leading multimodal systems such as QwenVL2.5 and InternVL3, all while being fully reproducible with open data. The project supports a wide range of research applications, from visual recognition and dense prediction to fine-grained multimodal understanding. Additionally, it includes several large-scale open datasets for both image and video perception. -
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Klavis AI
MCP integration platforms for AI agents to use tools at any scale
Klavis AI is a Y Combinator X25-backed open-source infrastructure platform that enables AI agents to reliably connect with external tools and services at scale through Model Context Protocol (MCP). Founded by ex-Google DeepMind and ex-Lyft engineers, Klavis provides 50+ production-ready MCP servers with enterprise OAuth support for GitHub, Slack, Gmail, Salesforce, Linear, Notion, and more. The flagship product Strata solves tool overload through progressive discovery, achieving +13% higher... -
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AutoCVE
Agent-driven automated CVE discovery platform for source code auditing
AutoCVE is an agent-driven platform for automating authorized source-code auditing and CVE discovery. It covers the workflow from project selection and repository import to vulnerability verification and submission-ready report generation. An orchestrator coordinates specialized agents for reconnaissance, scanning, triage, deep analysis, verification, and final consolidation. Users can choose enhanced scanning, intelligent auditing, or comprehensive auditing based on speed and depth... -
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VulnClaw
Based on AI Agent + MCP toolchain + penetration Skill orchestration
VulnClaw is an AI-powered penetration testing agent that turns natural language security goals into structured testing workflows. It combines LLM agents, MCP toolchains, penetration testing skills, and command-line automation to support authorized security assessments. The project can guide information gathering, vulnerability discovery, validation, and report generation while keeping the workflow organized through sessions and tools. Its newer architecture uses a goal-driven solving engine... -
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OpenSquilla
Token-Efficient AI Agent with same budget, higher intelligence density
OpenSquilla is a token-efficient microkernel AI agent runtime designed for CLI, web UI, and chat-based workflows. It routes each turn through a shared loop that can select lower-cost models when appropriate while preserving tool dispatch, retries, memory, and decision logging. The project supports multiple LLM providers through a pluggable provider layer, making it adaptable to different model ecosystems. It includes persistent memory, built-in web search, on-device embeddings, and... -
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Kaggle Python Docker
Kaggle Python docker image
Kaggle Python Docker is Kaggle’s official Docker image repository for the Python environment used by Kaggle Notebooks. It contains the Dockerfiles and build configuration for both CPU-only and GPU-enabled notebook images. The project helps users understand, reproduce, and test against the same Python environment that powers Kaggle’s cloud notebooks. It includes a large curated package set for data science, machine learning, visualization, notebooks, and scientific computing. The images are...