%20--%3e%3cdefs%3e%3cstyle%3e%20.st0%20{%20fill:%20%23061b40;%20}%20.st1%20{%20fill:%20%23306af1;%20}%20.st2%20{%20fill:%20%235ce5cf;%20}%20%3c/style%3e%3c/defs%3e%3cg%3e%3cpath%20class='st0'%20d='M55,10.5h9v3h-9v9h12V7.5h-12v3ZM64,19.5h-6v-3h6v3Z'/%3e%3cpolygon%20class='st0'%20points='69%2016.5%2078%2016.5%2078%2019.5%2069%2019.5%2069%2022.5%2081%2022.5%2081%2013.5%2072%2013.5%2072%2010.5%2081%2010.5%2081%207.5%2069%207.5%2069%2016.5'/%3e%3cpolygon%20class='st0'%20points='95%2010.5%2095%207.5%2083%207.5%2083%2022.5%2095%2022.5%2095%2019.5%2086%2019.5%2086%2016.5%2095%2016.5%2095%2013.5%2086%2013.5%2086%2010.5%2095%2010.5'/%3e%3cpath%20class='st0'%20d='M40,1.5v21h11.6l1.4-1.4v-7.6h0c0,0-1.4-1.5-1.4-1.5l1.4-1.4V2.9l-1.4-1.4h-11.6ZM50,19.5h-7v-6h7v6ZM50,10.5h-7v-6h7v6Z'/%3e%3c/g%3e%3cpath%20class='st1'%20d='M23.1,24L14.7,4.8l-4.9,11.2h3.8l-1.8,4H3.3L12.1,0H2C.9,0,0,.9,0,2v20c0,1.1.9,2,2,2h21.1Z'/%3e%3cpath%20class='st2'%20d='M34,0h-16.8l10.6,24h6.2c1.1,0,2-.9,2-2V2C36,.9,35.1,0,34,0ZM32.5,20h-4V4h4v16Z'/%3e%3c/svg%3e)
Infini Megrez
Overview :
Infini-Megrez is an edge multimodal understanding model developed by Wuwen Xinqun, based on the Megrez-3B-Instruct extension. It excels in comprehending and analyzing three types of modal data: images, text, and audio, achieving optimal accuracy in image understanding, language comprehension, and speech recognition. The model is optimized for a synergistic hardware-software collaboration, ensuring that its structural parameters are highly compatible with mainstream hardware, achieving inference speeds up to 300% faster than similar precision models. It is straightforward to use, based on the original LLaMA architecture, allowing developers to deploy the model on various platforms without modifications, minimizing the complexity of secondary development. Additionally, Infini-Megrez provides a complete WebSearch solution, enabling the model to automatically determine when to trigger search calls, switch between searching and dialogue, and deliver enhanced summarization results.
Target Users :
Infini-Megrez targets developers, data scientists, and enterprise users, especially those requiring rapid and high-precision multimodal data processing at the edge. Its user-friendly design and fast inference capabilities make it ideal for users who need quick deployment and integration into existing systems. Additionally, for enterprises handling large volumes of images, text, and speech data, Infini-Megrez offers powerful data processing capabilities and efficient solutions.
Use Cases
Example 1: Developers use the Infini-Megrez model for image recognition and voice interaction to create intelligent home control systems.
Example 2: Enterprises utilize the Infini-Megrez model for OCR recognition and text analysis to optimize customer service processes.
Example 3: Data scientists employ the Infini-Megrez model for multimodal data analysis, enhancing the accuracy of market predictions.
Features
? Image Understanding: Builds image tokens based on SigLip-400M, achieving an average score of 66.2 on the OpenCompass leaderboard, surpassing models with larger parameter scales.
? Language Understanding: Maintains text processing capabilities, with accuracy changes of less than 2% compared to unimodal versions, retaining optimal performance across multiple test sets.
? Speech Understanding: Utilizes Qwen2-Audio/whisper-large-v3 as the encoder for speech input, supporting both Chinese and English voice input and multi-turn dialogues.
? Quick Start: Provides detailed guidelines for online experience and local deployment, enabling users to start using it quickly.
? High-Speed Inference: Achieves a decoding speed of 1294.9 tokens/s in an NVIDIA H100 environment.
? Hardware-Software Synergy: Optimized through hardware-software collaboration, ensuring high alignment with mainstream hardware for leading inference speed.
? User-Friendly: Based on the original LLaMA architecture, deployable across various platforms without modification.
How to Use
1. Visit the Infini-Megrez GitHub page to download the model and related code.
%20--%3e%3cdefs%3e%3cstyle%3e%20.st0%20{%20fill:%20%230080ff;%20}%20%3c/style%3e%3c/defs%3e%3cpath%20class='st0'%20d='M16.2,11.1c.4.5.4,1.2,0,1.8l-4.7,7.1h-3.8l5.3-8L7.6,4h3.8l4.7,7.1Z'/%3e%3c/svg%3e)
2. Follow the provided guidelines to install the necessary environment and dependencies.
3. Refer to the sample code to load the model and deploy it locally.
4. Prepare input data, including image, text, and audio files.
5. Call the model interface and pass in the prepared data for inference.
6. Obtain the model's output results and perform post-processing as needed.
7. Adjust model parameters based on feedback to optimize performance.
Featured AI Tools
Gemini
Gemini is the latest generation of AI system developed by Google DeepMind. It excels in multimodal reasoning, enabling seamless interaction between text, images, videos, audio, and code. Gemini surpasses previous models in language understanding, reasoning, mathematics, programming, and other fields, becoming one of the most powerful AI systems to date. It comes in three different scales to meet various needs from edge computing to cloud computing. Gemini can be widely applied in creative design, writing assistance, question answering, code generation, and more.
AI Model
11.4M
Chinese Picks
Liblibai
LiblibAI is a leading Chinese AI creative platform offering powerful AI creative tools to help creators bring their imagination to life. The platform provides a vast library of free AI creative models, allowing users to search and utilize these models for image, text, and audio creations. Users can also train their own AI models on the platform. Focused on the diverse needs of creators, LiblibAI is committed to creating inclusive conditions and serving the creative industry, ensuring that everyone can enjoy the joy of creation.
AI Model
6.9M