This is the SVDQ quantization version of the Project0 model, a text-to-image model created based on Flux Dev and Flux Krea. The model offers various quantization formats, optimized for different GPU architectures, including INT4 and FP4 quantization versions, suitable for both Blackwell and non-Blackwell GPU users.

MultimodalDiffusersEnglish

This is a LyCORIS adapter based on the Qwen/Qwen-Image model, specifically designed for text-to-image and image-to-image generation tasks. The model did not use validation prompts during training and adopted optimized training configurations and quantization techniques.

MultimodalDiffusers

A quantized version of the text-to-image generation model developed based on Flux.1, using SVDQ quantization technology, offering two quantization formats, INT4 and FP4, suitable for efficient image generation on different hardware platforms.

Computer VisionDiffusersEnglish

A quantized version of the text-to-image generation model developed based on Flux.1-Dev of J1B, optimized using SVDQuant technology, offering two quantization formats, INT4 and FP4, suitable for users with different GPU architectures.

Computer VisionDiffusersMultiple Languages

PixelWave is a text-to-image model developed based on Flux.1. It has been optimized through Nunchaku quantization (SVDQ), providing an efficient image generation solution for users with different GPU configurations.

Computer VisionDiffusersEnglish

LibreFLUX-ControlNet is a text-to-image generation model based on the ControlNet architecture, using LibreFLUX as the base Transformer model. This model is trained on the SA1B dataset and can generate high-quality image content based on text prompts and control images.

Computer VisionDiffusers

CenKreChro-SVDQ is a quantized version of the text-to-image generation model merged based on Chroma and Flux Krea. It is optimized using SVDQuant technology and offers two quantization formats, INT4 and FP4, suitable for different generations of GPU hardware respectively.

Computer VisionDiffusersEnglish

FIBO is the first open-source text-to-image model specifically trained for long structured descriptions, setting new standards for controllability, predictability, and feature decoupling. This model has 8 billion parameters and is trained using only licensed data, supporting the needs of professional workflows.

MultimodalDiffusersEnglish

An anime-style model focused on text-to-image generation, capable of generating 2D illustrations, character portraits, and character settings featuring cute girl images. The images have characteristics such as dynamic poses, clear structures, and strong lighting.

Computer VisionDiffusersEnglish

This is a LoRA (Low-Rank Adaptation) model trained based on the Qwen-Image model, specifically designed for text-to-image generation tasks. This project is trained using AI Toolkit and can convert text descriptions into high-quality images, supporting use in various image generation tools.

MultimodalDiffusers

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

This is a LyCORIS adapter based on the PixArt-900M-1024 model, specifically designed for text-to-image conversion tasks. This model can generate corresponding images based on the input text description and supports image generation at multiple resolutions.

Computer VisionDiffusers

svizz is a text-to-image generation model based on LoRA technology. It uses LyliaEngine/Pony_Diffusion_V6_XL as the base model and can generate high-quality image content through specific trigger words.

Computer VisionDiffusers

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

lans_v1 - lora is a text-to-image conversion model trained using the AI Toolkit by Ostris based on the Qwen/Qwen-Image model. It is optimized using LoRA technology and has good image generation capabilities.

MultimodalDiffusers

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

Noobai-XL-1.0 is a text-to-image generation model based on the diffusers library, specifically designed for generating anime-style girl images. This model was created by HetaKoneko, based on Laxhar/noobai-XL-1.0, and can generate anime images with a unique style.

Computer VisionDiffusersEnglish

This is a text-to-image conversion model trained based on the Qwen-Image base model, specifically designed to generate images in the style of the Day of The Tentacle game background. The model can generate unique cartoon-style images with bright colors and exaggerated lines.

MultimodalDiffusers

The Earth & Dusk project is a text-to-image conversion project based on the OnomaAIResearch/Illustrious-xl-early-release-v0 base model, which uses the diffusers library to generate images. This project focuses on art creation and is licensed under the CREATIVE ML OPEN RAIL M license, supervised by 0FTH3N1GHT PRODUCTIONS.

Computer VisionDiffusersMultiple Languages