Showing 42 open source projects for "stable-diffusion-webui"

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  • Automate contact and company data extraction Icon
    Automate contact and company data extraction

    Build lead generation pipelines that pull emails, phone numbers, and company details from directories, maps, social platforms. Full API access.

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  • 1
    Google DeepMind GraphCast and GenCast

    Google DeepMind GraphCast and GenCast

    Global weather forecasting model using graph neural networks and JAX

    ...The repository provides complete example code for running and training both GraphCast and GenCast, two models introduced in DeepMind’s research papers. GraphCast is designed to perform high-resolution atmospheric simulations using the ERA5 dataset from ECMWF, while GenCast extends the approach with diffusion-based ensemble forecasting for probabilistic weather prediction. Both models are built on JAX and integrate advanced neural architectures capable of learning from multi-scale geophysical data represented on icosahedral meshes. The package includes pretrained model weights, normalization statistics, and demonstration notebooks that allow users to replicate and fine-tune weather forecasting experiments in Colab or on Google Cloud TPUs and GPUs.
    Downloads: 8 This Week
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  • 2
    Qwen3-Omni

    Qwen3-Omni

    Qwen3-omni is a natively end-to-end, omni-modal LLM

    ...It achieves state-of-the-art results: across 36 audio and audio-visual benchmarks, it hits open-source SOTA on 32 and overall SOTA on 22, outperforming or matching strong closed-source models such as Gemini-2.5 Pro and GPT-4o. To reduce latency, especially in audio/video streaming, Talker predicts discrete speech codecs via a multi-codebook scheme and replaces heavier diffusion approaches.
    Downloads: 4 This Week
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  • 3
    NVIDIA Isaac GR00T

    NVIDIA Isaac GR00T

    NVIDIA Isaac GR00T N1.5 is the world's first open foundation model

    NVIDIA Isaac‑GR00T N1.5 is an open-source foundation model engineered for generalized humanoid robot reasoning and manipulation skills. It accepts multimodal inputs—such as language and images—and uses a diffusion transformer architecture built upon vision-language encoders, enabling adaptive robot behaviors across diverse environments. It is designed to be customizable via post-training with real or synthetic data. The vision-language model remains frozen during both pretraining and finetuning, preserving language understanding and improving generalization. ...
    Downloads: 0 This Week
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  • 4
    GLM-4.7

    GLM-4.7

    Advanced language and coding AI model

    GLM-4.7 is an advanced agent-oriented large language model designed as a high-performance coding and reasoning partner. It delivers significant gains over GLM-4.6 in multilingual agentic coding, terminal-based workflows, and real-world developer benchmarks such as SWE-bench and Terminal Bench 2.0. The model introduces stronger “thinking before acting” behavior, improving stability and accuracy in complex agent frameworks like Claude Code, Cline, and Roo Code. GLM-4.7 also advances “vibe...
    Downloads: 683 This Week
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  • Desktop and Mobile Device Management Software Icon
    Desktop and Mobile Device Management Software

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  • 5
    Style Aligned

    Style Aligned

    Official code for Style Aligned Image Generation via Shared Attention

    ...The repository provides reproducible scripts, reference prompts, and guidance for tuning strengths so users can dial in subtle retouches or bolder substitutions. Because it builds on widely used diffusion checkpoints, creators can integrate it without training or dataset collection.
    Downloads: 0 This Week
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  • 6
    DINOv3

    DINOv3

    Reference PyTorch implementation and models for DINOv3

    DINOv3 is the third-generation iteration of Meta’s self-supervised visual representation learning framework, building upon the ideas from DINO and DINOv2. It continues the paradigm of learning strong image representations without labels using teacher–student distillation, but introduces a simplified and more scalable training recipe that performs well across datasets and architectures. DINOv3 removes the need for complex augmentations or momentum encoders, streamlining the pipeline while...
    Downloads: 20 This Week
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  • 7
    DiffRhythm

    DiffRhythm

    Di♪♪Rhythm: Blazingly Fast & Simple End-to-End Song Generation

    DiffRhythm is an open-source, diffusion-based model designed to generate full-length songs. Focused on music creation, it combines advanced AI techniques to produce coherent and creative audio compositions. The model utilizes a latent diffusion architecture, making it capable of producing high-quality, long-form music. It can be accessed on Huggingface, where users can interact with a demo or download the model for further use.
    Downloads: 13 This Week
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  • 8
    Step-Audio 2

    Step-Audio 2

    Multi-modal large language model designed for audio understanding

    Step-Audio2 is an advanced, end-to-end multimodal large language model designed for high-fidelity audio understanding and natural speech conversation: unlike many pipelines that separate speech recognition, processing, and synthesis, Step-Audio2 processes raw audio, reasons about semantic and paralinguistic content (like emotion, speaker characteristics, non-verbal cues), and can generate contextually appropriate responses — including potentially generating or transforming audio output. It...
    Downloads: 0 This Week
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  • 9
    MiniMax-M1

    MiniMax-M1

    Open-weight, large-scale hybrid-attention reasoning model

    MiniMax-M1 is presented as the world’s first open-weight, large-scale hybrid-attention reasoning model, designed to push the frontier of long-context, tool-using, and deeply “thinking” language models. It is built on the MiniMax-Text-01 foundation and keeps the same massive parameter budget, but reworks the attention and training setup for better reasoning and test-time compute scaling. Architecturally, it combines Mixture-of-Experts layers with lightning attention, enabling the model to...
    Downloads: 0 This Week
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  • 10
    ControlNet

    ControlNet

    Let us control diffusion models

    ...The project includes many trained model variants that accept different types of conditioning (e.g., canny edge input, normal maps, skeletal pose) and produce improved fidelity in stable diffusion outputs. It is widely adopted in the community as a go-to tool for semi-automatic image generation workflows, especially when users want structure plus creative freedom.
    Downloads: 3 This Week
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  • 11
    Warlock-Studio

    Warlock-Studio

    Suite with Real-ESRGAN, BSRGAN , RealESRNet, IRCNN, GFPGAN & RIFE.

    v5.1.1. Warlock-Studio is a Windows application that uses Real-ESRGAN, BSRGAN, IRCNN, GFPGAN, RealESRNet, RealESRAnime and RIFE Artificial Intelligence models to upscale, restore faces, interpolate frames and reduce noise in images and videos. the application supports GPU acceleration (including multi-GPU setups) and offers batch processing for large workloads. It includes drag-and-drop handling for single or multiple files, optional pre-resize functions, and an automatic tiling system...
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    Downloads: 19 This Week
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  • 12
    Consistency Models

    Consistency Models

    Official repo for consistency models

    consistency_models is the repository for Consistency Models, a new family of generative models introduced by OpenAI that aim to generate high-quality samples by mapping noise directly into data — circumventing the need for lengthy diffusion chains. It builds on and extends diffusion model frameworks (e.g. based on the guided-diffusion codebase), adding techniques like consistency distillation and consistency training to enable fast, often one-step, sample generation. The repo is implemented in PyTorch and includes support for large-scale experiments on datasets like ImageNet-64 and LSUN variants. ...
    Downloads: 0 This Week
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  • 13
    DiT (Diffusion Transformers)

    DiT (Diffusion Transformers)

    Official PyTorch Implementation of "Scalable Diffusion Models"

    ...DiT achieves strong results on benchmarks like ImageNet and LSUN while being architecturally simple and highly modular. It supports variable resolution, conditioning on class or text embeddings, and integration with latent autoencoders (like those used in Stable Diffusion).
    Downloads: 1 This Week
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  • 14
    Stable-Dreamfusion

    Stable-Dreamfusion

    Text-to-3D & Image-to-3D & Mesh Exportation with NeRF + Diffusion

    A pytorch implementation of the text-to-3D model Dreamfusion, powered by the Stable Diffusion text-to-2D model. This project is a work-in-progress and contains lots of differences from the paper. The current generation quality cannot match the results from the original paper, and many prompts still fail badly! Since the Imagen model is not publicly available, we use Stable Diffusion to replace it (implementation from diffusers).
    Downloads: 0 This Week
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  • 15
    Chinese-LLaMA-Alpaca-2 v2.0

    Chinese-LLaMA-Alpaca-2 v2.0

    Chinese LLaMA & Alpaca large language model + local CPU/GPU training

    This project has open-sourced the Chinese LLaMA model and the Alpaca large model with instruction fine-tuning to further promote the open research of large models in the Chinese NLP community. Based on the original LLaMA , these models expand the Chinese vocabulary and use Chinese data for secondary pre-training, which further improves the basic semantic understanding of Chinese. At the same time, the Chinese Alpaca model further uses Chinese instruction data for fine-tuning, which...
    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
    InfoGAN

    InfoGAN

    Code for reproducing key results in the paper

    ...The repository includes code for experiments (e.g. on MNIST), launcher scripts, and some tests. It depends on a development version of TensorFlow (the code expects features not in older stable releases), and also uses other libraries like prettytensor and progressbar.
    Downloads: 0 This Week
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