34 projects for "diffusion" with 2 filters applied:

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  • 1
    VideoCrafter2

    VideoCrafter2

    Overcoming Data Limitations for High-Quality Video Diffusion Models

    ...It features models for both text-to-video and image-to-video generation. The system is optimized for generating videos from textual descriptions or still images, leveraging advanced diffusion models. VideoCrafter2, an upgraded version, improves on its predecessor by enhancing motion dynamics and concept combinations, especially in low-data scenarios. Users can explore a wide range of creative possibilities, producing cinematic videos that combine artistic styles and real-world scenes.
    Downloads: 16 This Week
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  • 2
    ControlNet

    ControlNet

    Let us control diffusion models

    ControlNet is a neural network architecture designed to add conditional control to text-to-image diffusion models. Rather than training from scratch, ControlNet “locks” the weights of a pre-trained diffusion model and introduces a parallel trainable branch that learns additional conditions—like edges, depth maps, segmentation, human pose, scribbles, or other guidance signals. This allows the system to control where and how the model should focus during generation, enabling users to steer layout, structure, and content more precisely than prompt text alone. ...
    Downloads: 1 This Week
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  • 3
    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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  • 4
    DiT (Diffusion Transformers)

    DiT (Diffusion Transformers)

    Official PyTorch Implementation of "Scalable Diffusion Models"

    DiT (Diffusion Transformer) is a powerful architecture that applies transformer-based modeling directly to diffusion generative processes for high-quality image synthesis. Unlike CNN-based diffusion models, DiT represents the diffusion process in the latent space and processes image tokens through transformer blocks with learned positional encodings, offering scalability and superior sample quality.
    Downloads: 0 This Week
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  • 5
    Anse

    Anse

    Supercharged experience for multiple models such as ChatGPT

    Anse is a modern, polished web UI built to serve as a unified interface for interacting with multiple AI-model backends (such as OpenAI’s models, DALL-E, Stable Diffusion, etc.). It emphasizes a clean, user-friendly experience and supports different conversation modes (single prompt, continuous dialogue, image generation, etc.). Anse uses client-side storage (IndexDB) to keep session history locally, prioritizing user privacy and avoiding automatic uploads of sensitive chat content. It is responsive and optimized for mobile, supports dark mode, and is designed for deployment in a variety of environments (Vercel, Netlify, Docker, etc.). ...
    Downloads: 0 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: 0 This Week
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  • 7
    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: 67 This Week
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  • 8
    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: 1 This Week
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  • 9
    NoobAI XL 1.1

    NoobAI XL 1.1

    Open, non-commercial SDXL model for quality image generation

    NoobAI XL 1.1 is a diffusion-based text-to-image generative model developed by Laxhar Dream Lab, fine-tuned from NoobAI XL 1.0 and built upon Illustrious-xl. It leverages the latest Danbooru and e621 datasets, using native tag captions to enhance visual fidelity, style accuracy, and prompt responsiveness. The model introduces refined quality tagging, ranking images by percentile to ensure results reflect modern aesthetic preferences.
    Downloads: 0 This Week
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