This is a LoRA fine-tuned model based on Qwen-Image-Edit-2509, specifically designed to solve the problem of secondary illumination processing for images. It can remove the illumination effect of the original image and regenerate realistic lighting and shadows for the target image according to the illumination and hue of the reference image, achieving the migration and fusion of image styles.

Computer VisionDiffusers

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

QwenEdit2509 is a specially designed Low - Rank Adaptation (LoRA) model focused on image color processing. It can desaturate images and reduce contrast, creating a flat, ungraded look similar to a camera's log profile while preserving details in highlights and shadows.

Computer VisionDiffusersEnglish

Sarashina2.2-Vision-3B is a large Japanese vision-language model trained by SB Intuitions. It is built based on Sarashina2.2-3B-Instruct and the SigLIP image encoder, and has powerful image-to-text conversion capabilities, supporting multimodal processing in Japanese and English.

MultimodalTransformersMultiple Languages

This is a quantized image-text-to-text model based on the Mistral architecture, with a parameter scale of 24B. It is specifically optimized and trained for instruction following tasks and supports multimodal input processing.

MultimodalGguf

The quantized version of the Huihui Qwen3-VL-4B thinking elimination model, optimized based on the Qwen3-VL-4B model, is specifically designed to eliminate the thinking chain reasoning process and can be used with the latest llama.cpp to provide efficient image-text to text processing capabilities.

MultimodalGguf

This is a quantized version based on the Huihui-Qwen3-VL-4B-Instruct-abliterated model, specifically designed for image-text to text conversion tasks. The model performance is optimized through quantization processing, providing support for multimodal applications.

MultimodalGguf

A quantized version of LightOnOCR-1B-1025, specifically designed for image-to-text tasks and widely used in fields such as document understanding and visual language processing. This model supports multiple European languages and is suitable for scenarios such as OCR, PDF processing, and table recognition.

MultimodalGgufMultiple Languages

Nanonets-OCR2-1.5B-exp GGUF is a powerful image-to-markdown OCR model that can convert documents into a structured markdown format and perform intelligent content recognition and semantic tagging. It supports the processing of multi-language documents.

MultimodalTransformersOther

This is a repaired image text-to-text model that solves the problem of inference failure of the original model in the latest Transformers version. This model is specifically designed for image recognition and text generation tasks and supports multimodal input processing.

MultimodalTransformersEnglish

Wenxin Edit 2509 Image Fusion LoRA is an image relighting LoRA model developed based on the Qwen-Image-Edit-2509 model. It can bring excellent light processing effects to images and achieve professional-level image relighting functions.

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

NVIDIA-Nemotron-Nano-VL-12B-V2-FP8 is a quantized vision-language model launched by NVIDIA, which adopts an optimized Transformer architecture and has undergone three-stage training on commercial images. This model supports single-image inference, has multilingual and multimodal processing capabilities, and is suitable for various scenarios such as image summarization and text-image analysis.

MultimodalTransformers

LFM2-VL-3B is a multimodal vision-language model developed by Liquid AI, built on the LFM2 backbone architecture. It has powerful visual understanding and reasoning capabilities, especially excelling in fine-grained perception tasks. This model can efficiently process text and image inputs and supports native image processing with a resolution of up to 512×512.

MultimodalTransformersMultiple Languages

Qwen3-VL-32B-Instruct is a powerful multimodal vision-language model developed based on the Qwen foundation model. After optimization and quantization, it is specifically optimized for Apple chip devices, providing efficient image-text processing capabilities.

MultimodalTransformers

Chandra is an advanced OCR model that can extract text from images and PDFs with high precision and preserve layout information. It supports output in Markdown, HTML, and JSON formats and performs excellently in handwriting recognition, form reconstruction, table processing, etc. It supports more than 40 languages.

MultimodalTransformers

Qwen3-VL-30B-A3B-Instruct-AWQ is a quantized version of the Qwen3-VL series, which has powerful visual language processing capabilities and supports tasks such as image understanding, video analysis, and multimodal reasoning. The model has significant improvements in text understanding, visual perception, spatial understanding, and long context processing.

MultimodalTransformers

Qwen3-VL-8B-Instruct is a multimodal vision-language model developed by the Qwen team, which supports the conversion from image-text to text. This version has undergone MLX 8-bit quantization processing and is specifically optimized for Apple silicon chips, improving the operating efficiency while maintaining performance.

MultimodalMlx

Granite Docling 258M is an image-text to text model based on the ONNX format, specifically designed for document understanding and processing. This model can convert the document content in images into a structured text format and supports multimodal input processing.

MultimodalTransformers

qwen_edit_photo_restore_v1-lora is a LoRA adapter trained based on the Qwen-Image-Edit model, specifically designed for image editing and restoration tasks. This model is trained using the AI Toolkit by Ostris, supports multiple mainstream AI platforms, and provides high-quality image processing capabilities.

MultimodalDiffusers