Showing 120 open source projects for "diffusion"

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  • 1
    MMGeneration

    MMGeneration

    MMGeneration is a powerful toolkit for generative models

    MMGeneration has been merged in MMEditing. And we have supported new-generation tasks and models. MMGeneration is a powerful toolkit for generative models, especially for GANs now. It is based on PyTorch and MMCV. The master branch works with PyTorch 1.5+. We currently support training on Unconditional GANs, Internal GANs, and Image Translation Models. Support for conditional models will come soon. A plentiful toolkit containing multiple applications in GANs is provided to users. GAN...
    Downloads: 0 This Week
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  • 2
    Stable Diffusion

    Stable Diffusion

    A latent text-to-image diffusion model

    Stable Diffusion is a widely used open-source latent text-to-image diffusion model developed by the CompVis group for generating high-quality images from natural language prompts. The model operates by conditioning a diffusion process on text embeddings produced by a CLIP text encoder, enabling detailed and controllable image synthesis. It was trained on large-scale image datasets and later fine-tuned to produce 512×512 images with strong visual fidelity.
    Downloads: 12 This Week
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  • 3
    DeepMozart

    DeepMozart

    Audio generation using diffusion models

    Audio generation using diffusion models in PyTorch. The code is based on the audio-diffusion-pytorch repository.
    Downloads: 3 This Week
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  • 4
    TradeMaster

    TradeMaster

    TradeMaster is an open-source platform for quantitative trading

    TradeMaster is a first-of-its-kind, best-in-class open-source platform for quantitative trading (QT) empowered by reinforcement learning (RL), which covers the full pipeline for the design, implementation, evaluation and deployment of RL-based algorithms. TradeMaster is composed of 6 key modules: 1) multi-modality market data of different financial assets at multiple granularities; 2) whole data preprocessing pipeline; 3) a series of high-fidelity data-driven market simulators for mainstream...
    Downloads: 0 This Week
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  • 5
    Riffusion

    Riffusion

    Real-time music generation using stable diffusion techniques AI

    Riffusion (hobby) is a Python-based open source library designed for real-time music and audio generation using stable diffusion techniques. Riffusion (hobby) works by generating and manipulating spectrogram images, which are then converted into playable audio clips, effectively bridging image-based diffusion models with sound synthesis. It implements a diffusion pipeline that supports prompt interpolation, allowing smooth transitions between different musical styles or prompts over time. ...
    Downloads: 2 This Week
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  • 6
    Point-E

    Point-E

    Point cloud diffusion for 3D model synthesis

    ...Its principal advantage is speed: it can generate 3D assets in just 1–2 minutes on a single GPU, which is significantly faster than many competing text-to-3D models. The model works via a two-stage diffusion approach: first, it uses a text → image diffusion network to produce a synthetic 2D view consistent with the prompt; then a second diffusion model converts that image into a 3D point cloud. While it does not match the fine detail of some slower methods, the tradeoff in speed makes it practical for prototyping and interactive 3D generation. ...
    Downloads: 3 This Week
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  • 7
    Minimal text diffusion

    Minimal text diffusion

    A minimal implementation of diffusion models for text generation

    A minimal implementation of diffusion models of text: learns a diffusion model of a given text corpus, allowing to generate text samples from the learned model. The main idea was to retain just enough code to allow training a simple diffusion model and generating samples, remove image-related terms, and make it easier to use. To train a model, run scripts/train.sh.
    Downloads: 0 This Week
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  • 8
    NÜWA - Pytorch

    NÜWA - Pytorch

    Implementation of NÜWA, attention network for text to video synthesis

    Implementation of NÜWA, state of the art attention network for text-to-video synthesis, in Pytorch. It also contains an extension into video and audio generation, using a dual decoder approach. It seems as though a diffusion-based method has taken the new throne for SOTA. However, I will continue on with NUWA, extending it to use multi-headed codes + hierarchical causal transformer. I think that direction is untapped for improving on this line of work. In the paper, they also present a way to condition the video generation based on segmentation mask(s). ...
    Downloads: 0 This Week
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  • 9
    G-Diffuser Bot

    G-Diffuser Bot

    Discord bot and Interface for Stable Diffusion

    The first release of the all-in-one installer version of G-Diffuser is here. This release no longer requires the installation of WSL or Docker and has a systray icon to keep track of and launch G-Diffuser components. The infinite zoom scripts have been updated with some improvements, notably a new compositer script that is hundreds of times faster than before. The first release of the all-in-one installer is here. It notably features much easier "one-click" installation and updating, as well...
    Downloads: 0 This Week
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  • 10
    DiffSinger

    DiffSinger

    Singing Voice Synthesis via Shallow Diffusion Mechanism

    DiffSinger is an open-source PyTorch implementation of a diffusion-based acoustic model for singing-voice synthesis (SVS) and also text-to-speech (TTS) in a related variant. The core idea is to view generation of a sung voice (mel-spectrogram) as a diffusion process: starting from noise, the model iteratively “denoises” while being conditioned on a music score (lyrics, pitch, musical timing).
    Downloads: 97 This Week
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  • 11
    Guided Diffusion

    Guided Diffusion

    Codebase for Diffusion Models Beat GANS on Image Synthesis

    The guided-diffusion repository is centered on diffusion models for image synthesis, with a focus on classifier guidance and improvements over earlier diffusion frameworks. It is derived from OpenAI’s improved-diffusion work, enhanced to include guided generation where a classifier (or other guidance mechanism) can steer sampling toward desired classes or attributes.
    Downloads: 0 This Week
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  • 12
    Disco Diffusion

    Disco Diffusion

    Notebooks, models and techniques for the generation of AI Art

    A frankensteinian amalgamation of notebooks, models, and techniques for the generation of AI art and animations. This project uses a special conversion tool to convert the Python files into notebooks for easier development. What this means is you do not have to touch the notebook directly to make changes to it. The tool being used is called Colab-Convert. Initial QoL improvements added, including user-friendly UI, settings+prompt saving, and improved google drive folder organization. Now...
    Downloads: 0 This Week
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  • 13
    AI Atelier

    AI Atelier

    Based on the Disco Diffusion, version of the AI art creation software

    Based on the Disco Diffusion, we have developed a Chinese & English version of the AI art creation software "AI Atelier". We offer both Text-To-Image models (Disco Diffusion and VQGAN+CLIP) and Text-To-Text (GPT-J-6B and GPT-NEOX-20B) as options. Making available complete source code of licensed works and modifications, which include larger works using a licensed work, under the same license.
    Downloads: 0 This Week
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  • 14
    StudioGAN

    StudioGAN

    StudioGAN is a Pytorch library providing implementations of networks

    ...Moreover, StudioGAN provides an unprecedented-scale benchmark for generative models. The benchmark includes results from GANs (BigGAN-Deep, StyleGAN-XL), auto-regressive models (MaskGIT, RQ-Transformer), and Diffusion models (LSGM++, CLD-SGM, ADM-G-U). StudioGAN is a self-contained library that provides 7 GAN architectures, 9 conditioning methods, 4 adversarial losses, 13 regularization modules, 6 augmentation modules, 8 evaluation metrics, and 5 evaluation backbones. Among these configurations, we formulate 30 GANs as representatives. Each modularized option is managed through a configuration system that works through a YAML file.
    Downloads: 0 This Week
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  • 15
    ruDALL-E

    ruDALL-E

    Generate images from texts. In Russian

    ...Try to create unique images together with generative artists using your own formulations. Ask generative artists to depict something special for you as well. The Kandinsky 2.0 model uses the reverse diffusion method and creates colorful images on various topics in a matter of seconds by text query in Russian and other languages. You can even combine different languages within a single query. This neural network has been developed and trained by Sber AI researchers in close collaboration with scientists from Artificial Intelligence Research Institute using joined datasets by Sber AI and SberDevices. ...
    Downloads: 0 This Week
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  • 16
    GLIDE (Text2Im)

    GLIDE (Text2Im)

    GLIDE: a diffusion-based text-conditional image synthesis model

    ...The project also offers sampling scripts and utilities for exploring how diffusion models can be applied to multimodal tasks. As one of the early diffusion-based text-to-image systems, glide-text2im laid important groundwork for later advances in generative AI research.
    Downloads: 1 This Week
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  • 17
    CLIP Guided Diffusion

    CLIP Guided Diffusion

    A CLI tool/python module for generating images from text

    A CLI tool/python module for generating images from text using guided diffusion and CLIP from OpenAI. Text to image generation (multiple prompts with weights). Non-square Generations (experimental) Generate portrait or landscape images by specifying a number to offset the width and/or height. Uses fewer timesteps over the same diffusion schedule. Sacrifices accuracy/alignment for quicker runtime. options: - 25, 50, 150, 250, 500, 1000, ddim25,ddim50,ddim150, ddim250,ddim500,ddim1000 (default: 1000) Prepending a number with ddim will use the ddim scheduler. e.g. ddim25 will use the 25 timstep ddim scheduler. ...
    Downloads: 1 This Week
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  • 18
    VQGAN-CLIP web app

    VQGAN-CLIP web app

    Local image generation using VQGAN-CLIP or CLIP guided diffusion

    VQGAN-CLIP has been in vogue for generating art using deep learning. Searching the r/deepdream subreddit for VQGAN-CLIP yields quite a number of results. Basically, VQGAN can generate pretty high-fidelity images, while CLIP can produce relevant captions for images. Combined, VQGAN-CLIP can take prompts from human input, and iterate to generate images that fit the prompts. Thanks to the generosity of creators sharing notebooks on Google Colab, the VQGAN-CLIP technique has seen widespread...
    Downloads: 1 This Week
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  • 19
    PixelCNN

    PixelCNN

    Code for the paper "PixelCNN++: A PixelCNN Implementation..."

    ...The project serves as both a research reference and a practical framework for experimenting with autoregressive generative models. Although archived, PixelCNN has influenced a wide range of later work in generative modeling, including advancements in image transformers and diffusion models.
    Downloads: 0 This Week
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  • 20

    scripthea

    Scripthea is designed to streamline of crafting prompts for T2I gen.

    Scripthea is a free, open-source Windows application designed to streamline the process of crafting prompts for text-to-image AI generators like Stable Diffusion. Scripthea offers a structured environment for building, testing, and refining prompts, making it an invaluable tool for artists, designers, and AI enthusiasts seeking greater control over their creative outputs. At its core, Scripthea simplifies prompt engineering by breaking down prompts into two components: cues (descriptive text) and modifiers (attributes like style, lighting, or artist references). ...
    Downloads: 0 This Week
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