MiniCPM-Llama3-V 2.5

Edge-deployable GPT-4V level multimodal large model

CommonProductProductivityMultimodalEdge Deployment

MiniCPM-Llama3-V 2.5 is the latest edge-deployable multimodal large model released by the OpenBMB project. It has 8B parameters, supports multimodal interaction in over 30 languages, and surpasses many commercial closed-source models in overall multimodal performance. The model achieves efficient deployment on terminal devices through technologies such as model quantization, CPU, NPU, and compilation optimization, and boasts excellent OCR capabilities, trustworthy behavior, and multilingual support.

Leading Performance: Averages 65.1 on the OpenCompass leaderboard
surpassing many commercial closed-source multimodal large models.
Excellent OCR Capability: Achieves a score of 725 on OCRBench
supports high-resolution image input and full-text OCR information extraction.
Trustworthy Behavior: Through RLAIF-V alignment technology
it exhibits a low hallucination rate and trustworthy multimodal behavior.
Multilingual Support: Supports multimodal capabilities in 30+ languages and enables cross-lingual generalization with a small amount of translation data.
Efficient Deployment: Achieves fast inference and image encoding on terminal devices through model quantization and compilation optimization techniques.
Easy Fine-tuning and Local WebUI Demo Deployment: Supports fine-tuning using the Huggingface Transformers library and the SWIFT framework.

This product is suitable for developers and enterprises that need to perform efficient multimodal interactions on edge devices
such as smartphones
tablets
etc.
as well as scenarios requiring image recognition

Conduct multimodal interaction between images and text on a smartphone.
Use the model for scene text recognition and information extraction.
Enable cross-lingual multimodal dialogue and content generation.

Clone the OpenBMB/MiniCPM-V code repository to your local machine.
Create a conda environment and install the required dependencies.
Run the local WebUI Demo according to your device type (e.g.
NVIDIA GPU
Mac MPS).

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