Hunyuan OCR is an end-to-end OCR expert VLM model driven by the Hunyuan native multimodal architecture. With a lightweight design of only 1 billion parameters, it has achieved state-of-the-art results in multiple industry benchmark tests. This model excels in handling complex multilingual document parsing and performs well in practical application scenarios such as text localization, open-domain information extraction, video subtitle extraction, and image translation.

MultimodalTransformersMultiple Languages

NuExtract 2.0 is a multimodal model developed by NuMind specifically for structured information extraction. It supports text and image input, has multilingual processing capabilities, and can extract structured information from input content according to a JSON template.

MultimodalTransformers

NuExtract 2.0 is a series of multimodal models specifically trained by NuMind for structured information extraction tasks. This 4B version is built on Qwen2.5-VL-3B-Instruct, supports text and image input, has multilingual processing capabilities, and can extract structured information from unstructured data.

MultimodalTransformers

Qwen2.5-Omni-3B-GGUF is an end-to-end multimodal model capable of perceiving various modal information such as text, images, audio, and video, and generating text and natural speech responses in a streaming manner.

MultimodalTransformersEnglish

Qwen2.5-Omni-7B is a powerful multimodal model that can perceive various modal information such as text, images, audio, and video, and generate text and natural voice responses in a streaming manner.

MultimodalTransformersEnglish

Qwen2.5-Omni-3B GGUF is a versatile multimodal model capable of processing various types of data such as text, images, audio, and video, providing efficient and accurate information processing and responses.

MultimodalTransformersEnglish

Lingshu is a multimodal large language model that performs excellently in the medical field. It can effectively process medical image and text information and demonstrates top - notch performance in medical Q&A and report generation tasks.

MultimodalTransformers

NuExtract 2.0 is a series of multimodal and multilingual models trained specifically for structured information extraction tasks, developed based on the QwenVL series of pre - trained models.

MultimodalTransformers

NuExtract 2.0 is a series of multimodal models specifically trained for structured information extraction tasks. It supports text and image inputs and has multilingual processing capabilities.

MultimodalTransformers

NuExtract 2.0 is a series of multimodal models specifically trained for structured information extraction tasks. It supports text and image inputs and has the ability to process multiple languages.

MultimodalTransformers

Glm-Edge-V-5B-GGUF is a multimodal model that supports the conversion of image and text into text. It supports bilingual processing in Chinese and English and can efficiently and accurately convert visual information into text descriptions.

MultimodalGgufMultiple Languages

ChemVLM-8B is an 8-billion-parameter multimodal large language model specifically designed for the chemistry domain, capable of processing both text and visual chemical information.

MultimodalTransformers

Kosmos-2 is a multimodal large language model capable of integrating visual information with language understanding to achieve image-to-text conversion and visual grounding tasks.

MultimodalTransformers

This is a fine-tuned multimodal LayoutLM model for document question answering tasks, capable of understanding both text and layout information in documents to answer questions.

MultimodalTransformersEnglish

MarkupLM is a multimodal pretrained model designed for rich visual document understanding and information extraction tasks, combining text and markup language information.

MultimodalTransformersEnglish