Microsoft’s latest release, Phi-3, introduces Phi-3-Vision-128k-instruct, a language model variant that has garnered attention for its impressive performance. This model, with 4 billion parameters, has shown superiority over GPT-4V and Gemini 1.0 Pro V in various benchmarks. This article delves into potential use cases for Phi-3-Vision-128k-instruct, showcasing its versatility in tasks such as Optical Character Recognition (OCR), image captions, table analysis, understanding figures, reading comprehension in scanned documents, and brand set requests.
To run Phi-3-Vision-128k-instruct locally, one can create a Conda Python environment and install necessary dependencies like torch and transformers. A code snippet is provided to facilitate running the model with examples for each use case.
In the Optical Character Recognition (OCR) example, the model accurately transcribes text from an image, demonstrating its capability in text extraction. For image captions, the model accurately describes the content of natural images, showcasing its proficiency in image understanding. The model also shows its ability to extract structured data from tables in machine-readable JSON format, making it suitable for table analysis tasks. Additionally, the model can interpret figures, providing concise descriptions of visual data.
Moreover, the model excels in reading comprehension tasks for scanned documents. By understanding the content of scanned text and answering questions based on it, Phi-3-Vision-128k-instruct showcases its comprehension abilities. Lastly, in brand set requests, the model accurately identifies and describes objects within an image, highlighting its interactive segmentation capabilities.
Phi-3-Vision-128k-instruct’s compact size, efficient performance, and zero-shot capabilities make it a valuable asset for various data science tasks, particularly in document analysis and understanding. Its suitability for deployment on consumer local GPUs, even after quantization, makes it accessible for a wide range of applications. While larger models may offer stronger linguistic skills, Phi-3-Vision-128k-instruct’s efficiency and effectiveness in tasks like OCR, document analysis, and understanding visual content set it apart in the MLLM landscape.
In conclusion, Phi-3-Vision-128k-instruct proves to be a versatile and powerful model for text and vision tasks, showcasing impressive performance across various applications. Its potential for specialized tasks and its efficiency in deployment make it a valuable tool for data science professionals looking to incorporate advanced language and vision capabilities into their workflows.
Article Source
https://towardsdatascience.com/6-real-world-uses-of-microsofts-newest-phi-3-vision-language-model-8ebbfa317fe8
