FLUX.2-dev is an image generation and editing model developed by black-forest-labs. It has been converted to the GGUF format, optimized specifically for image generation tasks, and adopts a diffusion model architecture. It supports use in the ComfyUI framework.

MultimodalGguf

Wan2.2 is a major upgrade version of the basic video model, focusing on integrating innovative technologies such as effective MoE architecture, efficient training strategies, and multimodal fusion into the video diffusion model, bringing more powerful and efficient solutions to the field of video generation.

MultimodalDiffusersMultiple Languages

UltraFlux is a diffusion transformer based on Flux, specifically designed for native 4K text-to-image generation. Through the collaborative design of data, architecture, and loss, it can maintain consistent image quality under various aspect ratios.

Computer VisionDiffusersEnglish

Stable Diffusion v2-1-base is a diffusion model for text-to-image generation, which has been fine-tuned with an additional 220k steps based on v2-base. This model can generate and modify images according to text prompts, support multiple resolution outputs, and is suitable for various fields such as artistic creation and educational research.

Computer VisionDiffusers

Stable Diffusion v2 is a text-to-image generation model based on the diffusion model, capable of generating and modifying images according to text prompts. This model is trained on a subset of the LAION-5B dataset, combining an autoencoder and a diffusion model, and is trained in the latent space, supporting multiple resolutions and tasks.

Computer VisionDiffusers

Stable Diffusion v2-1-unclip is a diffusion model fine-tuned based on Stable Diffusion 2.1. It can accept text prompts and CLIP image embeddings, and is used to create image variants or be used in combination with the text-to-image CLIP prior.

MultimodalDiffusers

This is an experimental Stable Diffusion 1.5 distillation model that uses the v-prediction flow matching method and geometric guided adaptive block weighting technology. It is currently in the research phase, the training is ongoing, and the results have not been verified.

Computer VisionDiffusers

BR-RM is an innovative two-round reasoning reward model that solves the 'judgment diffusion' problem in traditional reward models through adaptive branching and branch-based reflection mechanisms, achieving industry-leading performance in multiple reward modeling benchmark tests.

Natural Language ProcessingTransformersEnglish

Based on Stable Diffusion XL, the UNet weights are fine-tuned using the Inversion-DPO method, combining direct preference optimization (DPO) technology and the inversion method to improve the quality and alignment of image generation in the diffusion model.

Computer VisionDiffusers

This is a LoRA adaptation weight based on the Stable Diffusion XL base model 1.0, specifically fine-tuned for a specific style and can be used to generate images with a specific artistic style.

Computer VisionDiffusers

XL-Sat-IOR is a text-to-image generation model based on the Stable Diffusion and Stable Diffusion XL architectures. It can generate images with a high degree of realism, rich colors, movie-like texture, fine details, excellent lighting and shadow effects, and vivid facial expressions.

Computer VisionDiffusersEnglish

Stable Diffusion v1-5 is a text-to-image generation model based on latent diffusion technology, capable of generating realistic images according to text descriptions. This model is trained on the LAION-2B dataset, supports English text input, and generates images with a resolution of 512x512.

MultimodalDiffusers

RND1 is an experimental diffusion language model with 30 billion parameters, adopting a sparse mixture of experts architecture. This model is converted from a pre-trained autoregressive base model, supporting diffusion-based text generation. Only 3 billion parameters are activated for each token, achieving a balance between computational efficiency and model capacity.

Natural Language ProcessingTransformers

This is a text-to-image generation model based on Stable Diffusion and Stable Diffusion XL technologies. It is specifically optimized for portrait, texture, and skin performance, capable of generating realistic and natural images.

Computer VisionDiffusersEnglish

This is a text-to-image generation model based on Stable Diffusion XL, optimized specifically for Asian-style image generation, capable of generating image works with realism and aesthetic appeal.

Computer VisionDiffusersEnglish

Nova Anime XL is a text - to - image generation model based on the Stable Diffusion XL architecture, specifically designed to generate high - quality images in various styles such as anime, fantasy, and landscapes. It combines the advantages of multiple excellent base models and performs outstandingly in terms of details, characters, backgrounds, and color representation.

Computer VisionDiffusersEnglish

Illustrious-xl-early-release-v0 is a text-to-image generation model based on the Stable Diffusion XL architecture, specifically optimized for anime and 2D illustration styles, capable of generating high-quality image works based on text descriptions.

Computer VisionDiffusersEnglish

Pandora is a diffusion model for generating realistic, high-quality mobile photography-style images. It adopts a two-stage training process and can generate mobile photography-style images with surprising effects.

Computer VisionDiffusersMultiple Languages

CoDA is a code generation language model based on diffusion models developed by Salesforce AI Research. It has the ability to understand bidirectional context and is specifically designed for powerful code generation and completion tasks. This model only has 1.7 billion parameters and achieves excellent code generation performance while maintaining low computational requirements.

Natural Language ProcessingTransformersEnglish

This is a LoRA model that fine-tunes SD3.5-Medium using the DiffusionNFT method. It adopts an innovative online reinforcement learning paradigm and performs excellently in the text-to-image generation task, significantly improving the generation quality and training efficiency.

Computer VisionDiffusers