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Puyu Lingbi - an open-source multimodal large model with performance comparable to GPT-4V.

Puyu Lingbi IXC-2.5 is a new generation of multimodal large-scale model developed by the Shanghai Artificial Intelligence Laboratory. It features a large-scale language model backend of 7 bytes. It can handle long contexts of up to 96KB and supports ultra-high-resolution images and fine-grained video...

What is the Puyu Lingbi IXC-2.5?

Puyu Lingbi IXC-2.5 is a new generation of multimodal large-scale model launched by the Shanghai Artificial Intelligence Laboratory, featuring a large-scale language model backend of 7B. It can handle long contexts of up to 96K, supports ultra-high resolution images and fine-grained video understanding, and can conduct multi-turn, multi-image dialogues. IXC-2.5 can also automatically write web page code based on instructions to create high-quality text and image articles. It performs exceptionally well in multimodal benchmark tests, with performance comparable to OpenAI GPT-4V.

Main functions of Puyu Lingbi IXC-2.5

  • Ultra-high resolution image understandingThe IXC-2.5 features a built-in 560×560 ViT visual encoder, capable of processing high-resolution images of any scale and providing more sensitive detail capture.
  • Fine-grained video understandingIt treats video as an ultra-high resolution composite image composed of tens to hundreds of frames, capturing the details of each frame through dense sampling and high resolution.
  • Multi-turn, multi-image dialogueIt supports free-form multi-turn, multi-image dialogue, enabling machines to engage in more natural multi-turn interactions with humans.
  • Web page creationIt automatically combines HTML, CSS, and JavaScript source code to create web pages based on text and image instructions.
  • Writing high-quality text and image articlesBased on Chain-of-Thought and Direct Preference Optimization technologies, IXC-2.5 can significantly improve the quality of articles when writing text and image content.

Technical Principles of Puyu Lingbi IXC-2.5

  • Multimodal learningIXC-2.5 combines visual and language models, enabling it to process and understand image and text data simultaneously, thus achieving the ability to create hybrid text and image content.
  • Large language model backendIt uses a large-scale language model of 7B as the backend, providing powerful text generation and understanding capabilities.
  • Ultra-high resolution image processingWith its 560×560 ViT (Vision Transformer) visual encoder, the IXC-2.5 can process high-resolution images and capture subtle features within them.
  • Fine-grained video understandingIXC-2.5 treats video content as an ultra-high-resolution image composed of multiple frames, and achieves a deep understanding of the video content through dense sampling and high-resolution analysis.
  • Multi-turn, multi-image dialogue capabilityIt supports processing and responding to multiple images in multi-turn dialogues, simulating human communication and providing a more natural interactive experience.

The project address for Puyu Lingbi IXC-2.5

How to use the Puyu Lingbi IXC-2.5 pen

  • Environmental preparationEnsure that the computing environment meets the requirements for running the IXC-2.5 model, with sufficient memory and computing power, and that the necessary dependency libraries are installed.
  • Get the modelVisit the GitHub project page for Puyu Lingbi IXC-2.5 and follow the instructions to download or clone the model's code repository to your local machine.
  • Install dependenciesInstall the required dependencies according to the project's README or documentation, which may include Python libraries, deep learning frameworks, etc.
  • Model loadingLoading a pre-trained IXC-2.5 model into the application. This involves using the API of the deep learning framework to load the model parameters.
  • Data preparationPrepare input data, including text, images, or videos. Ensure the data format meets the model's input requirements.
  • Function callDepending on the needs, different functions of the model can be invoked, such as image understanding, video analysis, multi-turn dialogue, or graphic creation.

Application scenarios of Puyu Lingbi IXC-2.5

  • Content creationAutomatically generates articles, stories, reports, etc. with pictures and text, suitable for news media, blogs, educational materials production, etc.
  • Educational SupportProviding learning materials that combine visual and textual elements in teaching enhances the learning experience and helps students better understand and remember complex concepts.
  • Marketing and AdvertisingDesign engaging ad content, combining images and copy, to increase ad appeal and conversion rates.
  • Entertainment and GamesIn video games or interactive entertainment, storylines and visual content are generated based on player behavior or choices.
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