D-ART - LoRA - Z-Image-Turbo is an image generation model based on the Tongyi-MAI/Z-Image-Turbo base model. It is a LoRA (Low-Rank Adaptation) adapter designed to inject a specific 'D-ART' artistic style into the generated images. This style is characterized by generating illustrations of confident and dynamic young female characters, especially emphasizing the curves and dynamic poses of the characters. Users can activate this style by using specific trigger words to generate diverse images with unified aesthetic features.

Computer VisionDiffusers

NewBie image Exp0.1 is an efficient basic image generation model developed based on the Next-DiT architecture, specifically designed for generating high-quality anime-style images. It integrates advanced text encoders and visual components, supports natural language and structured tag input, and is a powerful tool for multi-character anime image generation.

Computer VisionDiffusersEnglish

Z-Image-Turbo is an image processing model quantized in FP8 E5M2 and E4M3FN formats. It is optimized based on the original Tongyi-MAI/Z-Image-Turbo model, significantly reducing the model size and inference resource requirements while maintaining performance.

MultimodalDiffusersEnglish

TomoroAI/tomoro-colqwen3-embed-4b is an advanced ColPali-style multimodal embedding model that can map text queries, visual documents (such as images, PDFs) or short videos into aligned multi-vector embeddings. This model combines the advantages of Qwen3-VL-4B-Instruct and Qwen3-Embedding-4B, performs excellently in the ViDoRe benchmark test, and significantly reduces the embedding space occupation.

MultimodalTransformersOther

Hunyuan Video-1.5 is a lightweight and high-performance video generation model. With only 8.3 billion parameters, it can provide top-notch video quality, significantly lowering the usage threshold. It can run smoothly on consumer-grade GPUs, supporting text-to-video and image-to-video generation, enabling every developer and creator to use it easily.

MultimodalDiffusersMultiple Languages

This is a quantized version of the Huihui Qwen3-VL-8B thinking ablated model. Based on the Qwen3-VL-8B architecture, it is specifically optimized and quantized for image-text conversion tasks and can be efficiently run through the llama.cpp tool.

MultimodalGguf

Qwen3-VL-2B-Instruct-GGUF is the GGUF quantized version of the multimodal vision-language model in the Tongyi Qianwen series. It has 2 billion parameters and supports the seamless integration of image understanding and text generation. It can run efficiently on devices such as CPUs and GPUs.

MultimodalTransformers

This is a quantized version of the Qwen3-VL-2B-Instruct model. The llama.cpp tool and the imatrix method are used to generate model files with multiple quantization levels, which are convenient for efficient operation in different hardware environments. This model is a multimodal vision-language model with 2B parameters, supporting the interaction between images and text.

MultimodalGguf

This is a Lora image fusion tool based on the Qwen-Edit model, specifically designed for image-to-image conversion tasks. It can achieve excellent image fusion effects and is particularly good at image editing functions such as white model to material conversion.

Computer VisionDiffusers

The Nanonets-OCR2-3B GGUF model is a powerful tool designed for document processing. It can intelligently convert various types of documents into structured Markdown format and has multiple advanced recognition and processing capabilities such as OCR, image-to-text conversion, PDF-to-Markdown conversion, and visual question answering.

MultimodalTransformersOther

Qwen3-VL-32B-Thinking-AWQ is a quantized version based on the Qwen/Qwen3-VL-32B-Thinking model and is the most powerful vision-language model in the Tongyi series. This model has excellent text understanding and generation capabilities, in-depth visual perception and reasoning capabilities, supports long context and video understanding, and is suitable for image-text to text conversion tasks.

MultimodalTransformers

This project provides the quantized GGUF version of the Wan 2.2 distilled model developed by the LightX2V team, specifically designed for image-to-video and video generation tasks. This version is optimized to work with tools such as ComfyUI-GGUF, providing efficient inference performance.

MultimodalGguf

The Ming-flash-omni preview version is a multimodal large model built on the Ling-Flash-2.0 sparse mixture of experts (MoE) architecture, with a total of 100B parameters and only 6B parameters activated per token. This model is a comprehensive upgrade based on Ming-Omni, showing significant improvements in multimodal understanding and generation, especially in speech recognition, image generation, and segmentation editing.

MultimodalDiffusersEnglish

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

This is a LoRA image generation model trained based on the Qwen/Qwen-Image-Edit-2509 base model, specifically designed for image-to-image conversion tasks, and trained using the AI Toolkit by Ostris.

Computer VisionDiffusers

kontext-dusk-3-lora is a LoRA image generation model trained based on the FLUX.1-Kontext-dev base model, specifically designed to generate images in the style of the twilight blue hour. This model is triggered by specific trigger words and supports the use of multiple mainstream AI image generation tools.

Computer VisionDiffusers

joywan-lora is a LoRA model trained based on AI Toolkit by Ostris, specifically designed for text-to-video and image generation tasks. It needs to be used in conjunction with the base model Wan-AI/Wan2.1-T2V-14B-Diffusers.

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 LoRA adapter trained based on the Wan2.1-T2V-14B model, specifically designed for text-to-video conversion tasks and providing enhanced capabilities for image generation. This model is trained using the AI Toolkit and requires a specific trigger word 'diddly' to activate image generation.

MultimodalDiffusers

pejawan22-lora is a LoRA model trained based on AI technology, specifically designed for generating specific images and can be integrated with various AI tools. Images are generated by the trigger word 'peja'.

MultimodalDiffusers