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

This project is the result of MXFP4_MOE quantization of the Qwen3-VL-30B-A3B-Thinking model. This model can achieve the conversion from image-text to text, providing a new solution for applications in related fields.

MultimodalGguf

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

This is a quantized version of the Qwen3-Coder-REAP-25B-A3B model from Cerebras. It uses the imatrix technology of llama.cpp for quantization, which can reduce the model storage space and computational resource requirements while maintaining the model performance.

Natural Language ProcessingGguf

This is the Llamacpp imatrix quantized version of the Ling-flash-2.0 model by inclusionAI. Through advanced quantization technology, it significantly reduces memory usage and computational requirements while maintaining model performance, thereby improving operational efficiency. It supports multiple quantization levels and is suitable for different hardware configurations.

Natural Language ProcessingGguf

This is a quantized version of the Ling-mini-2.0 model from inclusionAI, quantized using the imatrix technology of llama.cpp. It offers various quantization options from 32.54GB BF16 to 4.66GB IQ2_XS and can run efficiently in multiple hardware environments.

Natural Language ProcessingGguf

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

DreamOmni2-GGUF is an image-to-image model that converts the xiabs/DreamOmni2-7.6B model to the GGUF format. It supports multimodal instruction editing and generation and follows the Apache-2.0 license.

MultimodalGguf

This is a LoRA model based on Qwen-Image-Edit-2509, specifically designed to accurately apply design patterns to people's shirts, providing new possibilities for image editing.

Computer VisionDiffusers

DeepSeek-OCR is an advanced optical character recognition model developed by DeepSeek AI, focusing on exploring the boundaries of visual text compression and capable of efficiently extracting and converting text content from images.

MultimodalSafetensorsOther

Qwen3-VL-TimeTravel is a version fine-tuned on the MBZUAI/TimeTravel dataset using the Unsloth library based on the Qwen3-VL-8B-Instruct model. This model is specifically designed to generate descriptions of historical cultural relic images and has professional capabilities in historical and cultural relic analysis.

MultimodalTransformersEnglish

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

This is the 8-bit quantized version of the Qwen3-VL-4B-Instruct model in MLX format, converted by mlx-community. This model is a multimodal vision-language model with 4 billion parameters, supporting image understanding and text generation tasks, and optimized for instruction following scenarios.

MultimodalMlx

This is a visual language model in MLX format converted from the Qwen3-VL-30B-A3B-Thinking model, supporting image understanding and multimodal dialogue, and optimized with bf16 precision.

MultimodalMlx

This is the GGUF quantized version of the AgentFlow agentflow-planner-7b model. It uses the imatrix technology of llama.cpp for quantization and offers multiple quantization levels, suitable for efficient inference under different hardware configurations.

Natural Language ProcessingGguf

This is the quantized version of TheDrummer's Cydonia-24B-v4.2.0 model, optimized using llama.cpp and imatrix technology. It provides multiple quantization type options for different hardware and requirements, facilitating users to run the model efficiently in different scenarios.

Natural Language ProcessingGguf

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

This is a quantized version of the Beck-4B model by gustavecortal. It uses the llama.cpp tool and the imatrix dataset for quantization optimization, providing a variety of quantization types from BF16 to IQ2_M, and can run efficiently in multiple hardware environments.

Natural Language ProcessingGguf

This is a quantized version of a large language model with 72B parameters. It uses the imatrix technology of llama.cpp for optimized quantization processing, providing multiple quantization levels to adapt to different hardware conditions and supporting operation in environments such as LM Studio and llama.cpp.

Natural Language ProcessingGguf

This is the quantized version of the YanoljaNEXT-Rosetta-12B-2510 model from Yanolja. It is quantized using the llama.cpp tool and the imatrix dataset, offering multiple quantization types to adapt to different hardware environments, significantly reducing resource consumption while maintaining model quality.

Natural Language ProcessingGguf