Search Results for "reference"
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Showing 165 open source projects for "reference"
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FLUX.2
Official inference repo for FLUX.2 models
FLUX.2 is a state-of-the-art open-weight image generation and editing model released by Black Forest Labs aimed at bridging the gap between research-grade capabilities and production-ready workflows. The model offers both text-to-image generation and powerful image editing, including editing of multiple reference images, with fidelity, consistency, and realism that push the limits of what open-source generative models have achieved. It supports high-resolution output (up to ~4 megapixels), which allows for photography-quality images, detailed product shots, infographics or UI mockups rather than just low-resolution drafts. FLUX.2 is built with a modern architecture (a flow-matching transformer + a revamped VAE + a strong vision-language encoder), enabling strong prompt adherence, correct rendering of text/typography in images, reliable lighting, layout, and physical realism, and consistent style/character/product identity across multiple generations or edits. -
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HunyuanVideo-I2V
A Customizable Image-to-Video Model based on HunyuanVideo
HunyuanVideo-I2V is a customizable image-to-video generation framework from Tencent Hunyuan, built on their HunyuanVideo foundation. It extends video generation so that given a static reference image plus an optional prompt, it generates a video sequence that preserves the reference image’s identity (especially in the first frame) and allows stylized effects via LoRA adapters. The repository includes pretrained weights, inference and sampling scripts, training code for LoRA effects, and support for parallel inference via xDiT. ... -
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Stable Diffusion Version 2
High-Resolution Image Synthesis with Latent Diffusion Models
Stable Diffusion (the stablediffusion repo by Stability-AI) is an open-source implementation and reference codebase for high-resolution latent diffusion image models that power many text-to-image systems. The repository provides code for training and running Stable Diffusion-style models, instructions for installing dependencies (with notes about performance libraries like xformers), and guidance on hardware/driver requirements for efficient GPU inference and training. -
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LLaMA 3
The official Meta Llama 3 GitHub site
...Practically, it functioned as a bridge between Llama 2 and later Llama releases by standardizing distribution and starter code for inference and fine-tuning. Teams still treat it as historical reference material for version lineage and migration notes. -
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OmniVoice
High-Quality Voice Cloning TTS for 600+ Languages
...Built on a diffusion language model-style architecture, it combines scalability with strong performance, enabling both natural-sounding voice synthesis and efficient inference speeds. One of its most notable capabilities is zero-shot voice cloning, allowing users to replicate a speaker’s voice using only a short reference audio clip. In addition, it supports voice design through configurable attributes such as gender, accent, pitch, and speaking style, giving users fine-grained control over generated speech. The system also includes advanced features like non-verbal expression tags and pronunciation overrides, enabling expressive and precise output. ... -
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HeartMuLa
A Family of Open Sourced Music Foundation Models
HeartMuLa is the open-source library and reference implementation for the HeartMuLa family of music foundation models, designed to support both music generation and music-related understanding tasks in a cohesive stack. At the center is HeartMuLa, a music language model that generates music conditioned on inputs like lyrics and tags, with multilingual support that broadens the range of lyric-driven use cases. -
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OpenVoice
Instant voice cloning by MIT and MyShell. Audio foundation model
OpenVoice is a versatile instant voice cloning system that can replicate a speaker’s tone color from just a short audio clip and then generate speech in multiple languages. It is designed not only to match the timbre of the reference voice, but also to give granular control over style parameters such as emotion, accent, rhythm, pauses, and intonation. The model supports cross-lingual and even zero-shot cross-lingual voice cloning, so a speaker recorded in one language can be made to speak naturally in others. Architecturally, OpenVoice separates “tone color” cloning from style control, which makes it easier to keep a consistent identity while flexibly changing prosody or language. ... -
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img2threejs
Rebuild the object in a reference image as a code-only, procedural
img2threejs is an open-source agent skill that rebuilds an object from one reference image as procedural Three.js code. It generates a TypeScript THREE.Group factory from primitives, procedural shaders, and generated geometry rather than extracting or downloading a mesh. The resulting hierarchy can include pivots, sockets, colliders, and destruction groups so the model is ready for interaction and animation. A staged pipeline evaluates suitability, defines a detailed specification, builds successive passes, renders browser previews, and compares them with the source image. ... -
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GenMedia Creative Studio
AI generative media user experience highlighting use of APIs
...The repository also includes experiments and MCP-related materials for connecting generative media capabilities to agent workflows. It is not an officially supported Google product, so it is best treated as a reference implementation and creative sandbox rather than a managed commercial service. -
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LLaMA Models
Utilities intended for use with Llama models
...Model lineages and size variants are documented externally (e.g., Llama 3.x and beyond), with this repo providing the “single source of truth” links and utilities. In practice, teams use llama-models as a reference when selecting variants, aligning licenses, and wiring in helper scripts for deployment. -
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clone-voice
A sound cloning tool with a web interface, using your voice
...It does not require an NVIDIA GPU to run basic tasks, although GPU acceleration can be used when available, making it accessible on modest machines. The tool supports around sixteen languages, including Chinese, English, Japanese, Korean, French, German, Italian, and others, and can capture reference voices directly from a microphone or from uploaded audio. -
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BigMac
An open-source toolkit for BigMac-style pipeline-parallel training
...This design reduces activation memory without bringing back cross-module pipeline bubbles. Its scheduler creates global operator plans, while its executor runs those plans through a shared schedule abstraction. A Megatron-Core reference backend and Qwen3 and Qwen3-VL tutorials help developers connect the approach to real training workflows. The simulator lets researchers visualize schedules, compare pipeline strategies, and model timing imbalances caused by compute cost, input size, or uneven stage partitioning. Profiling tools also expose per-operator traces for diagnosing pipeline performance before or during experiments. -
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HunyuanVideo-Avatar
Tencent Hunyuan Multimodal diffusion transformer (MM-DiT) model
...Innovations include a character image injection module, an Audio Emotion Module for transferring emotion cues, and a Face-Aware Audio Adapter to isolate audio effects on faces, enabling multiple characters to be animated in a scene. Character image injection module for better consistency between training and inference conditioning. Emotion control by extracting emotion reference images and transferring emotional style into video sequences. -
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Real-Time Voice Cloning
Clone a voice in 5 seconds to generate arbitrary speech in real-time
...In the first stage, short audio clips are converted into a fixed-dimensional speaker embedding that captures voice characteristics; this embedding is then used by a Tacotron-style synthesizer to generate spectrograms from text, which a WaveRNN-based vocoder finally turns into audio. The repo includes both a command-line demo and a graphical “toolbox” application where you can load reference voices, type text, and hear the synthesized results interactively. It also provides scripts for preprocessing datasets (such as LibriSpeech), training each of the three components. -
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Three.js Object Sculptor
Codex plugin that turns attached object images into code-only
...Generated models include meaningful sockets and anchors for animation, transformation, physics, and destruction. Reference and rendered screenshots can be combined for AI vision review and scored self-correction. The workflow targets browser-friendly props and stylized reconstructions rather than photogrammetry or exact mesh extraction. -
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NVIDIA AI Blueprint
Suite of reference architectures for building GPU-accelerated vision
...It supports workflows such as natural-language video search, visual question answering, long-video summarization, clip retrieval, verified alerts, and incident analysis. It is designed for technical users who need deployable reference architectures for smart spaces, warehouse automation, SOP validation, monitoring, and operational video analytics. The repository includes Python agent code, Docker Compose deployment configurations, skills, scripts, and a Next.js-based UI. -
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VoxCPM2
Tokenizer-Free TTS for Multilingual Speech Generation
...VoxCPM stands out for its ability to perform voice cloning with minimal input, capturing not only the speaker’s timbre but also nuanced features such as rhythm, accent, and emotional delivery. It also introduces voice design capabilities, allowing users to generate entirely new voices from natural language descriptions without requiring reference audio. -
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NVIDIA Generative AI Examples
Generative AI reference workflows
NVIDIA GenerativeAIExamples is an open-source repository that provides practical reference implementations and example workflows for building generative AI applications using NVIDIA’s software ecosystem. The project is designed to help developers accelerate the development of AI applications by providing ready-to-run pipelines, notebooks, and tools that demonstrate how to integrate large language models into real-world systems. -
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Google Research
This repository contains code released by Google Research
Google Research is a massive monorepo that hosts a wide range of research code released by Google Research teams across machine learning, artificial intelligence, robotics, natural language processing, and other advanced domains. Rather than being a single framework, the repository serves as a centralized collection of experimental projects, reference implementations, and reproducible research artifacts. It is intended primarily for researchers and advanced practitioners who want to explore cutting-edge techniques directly from the teams that developed them. The repository includes datasets, training scripts, and model implementations that support academic study and applied experimentation. ... -
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InstantCharacter
Personalize Any Characters with a Scalable Diffusion Transformer
InstantCharacter is a tuning-free diffusion transformer framework created by Tencent Hunyuan / InstantX team, which enables generating images of a specific character (subject) from a single reference image, preserving identity and character features. Uses adapters, so full fine-tuning of the base model is not required. Demo scripts and pipeline API (via infer_demo.py, pipeline.py) included. It works by adapting a base image generation model with a lightweight adapter so that you can produce character-preserving generations in various downstream tasks (e.g. changing pose, clothing, scene) without needing full model fine-tuning. ... -
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Finance
150+ quantitative finance Python programs
...The project focuses on explaining key principles used in finance and investment analysis, including topics such as financial statements, valuation models, portfolio theory, and financial markets. The repository is designed as a study reference for students and professionals who want to understand financial systems and the analytical frameworks used in financial decision-making. It organizes concepts into structured documents that explain both theoretical principles and practical calculations used in finance. The materials often include definitions, formulas, conceptual explanations, and examples to help readers understand how financial models and instruments function in real markets. -
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LuxTTS
A high-quality rapid TTS voice cloning model
...It implements a lightweight architecture based on ZipVoice and optimized sampling techniques so that it can generate speech at speeds up to roughly 150 times real-time on a single GPU and faster than real-time on CPU, all while producing audio at high fidelity with 48 kHz quality. 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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VoxCPM
TTS for Context-Aware Speech Generation and True-to-Life Voice Cloning
...Trained on a large 1.8-million-hour bilingual corpus, VoxCPM can infer appropriate speaking style from context, dynamically adjusting intonation, rhythm, and emotional tone. It supports zero-shot voice cloning from a short reference audio clip, capturing timbre, accent, and pacing to closely mimic a target speaker without per-speaker fine-tuning. -
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OuteTTS
Interface for OuteTTS models
...It also includes a notion of speaker profiles: you can create a speaker from a short audio sample, save it as JSON, and reuse it for consistent voice identity across generations and sessions. For best quality, the model is designed to work with a reference speaker clip and will inherit emotion, style, and accent from that reference. -
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Agent Skills
Specification and documentation for Agent Skills
...The central goal is portability: you can write a skill once and reuse it across different agent runtimes and developer tools that implement the format. This repo serves as the canonical reference for how skills should be structured, what metadata they should include, and how an SDK can load and apply them consistently. It also includes supporting materials like guides and examples so builders can create skills that are predictable, testable, and shareable with teams.
