HyperCLOVAX-SEED-Vision-Instruct-3B - A Korean Model - Install and Test Locally
AI Summary
Summary of Hyper Cloex Seed Model
Overview
- Presenter: Bahad Miza
- Focus: Hyper Cloex model for Korean language tasks with visual token optimization.
Installation Steps
- Create a virtual environment (using Conda).
- Install prerequisites:
torch,torchvision, etc.- Utilize Nvidia H100 (80 GB VRAM) on Ubuntu.
Model Features
- Architecture: Lightweight and efficient for various tasks such as visual question answering.
- Training Data Cutoff: Before August 2024.
- Context Length: 16,000 tokens.
- Visual Processing: Supports up to 1.29 million pixels at 378x378 resolution.
- Performance Focus: Aims for an optimal balance between performance and efficiency.
Testing
- First Test: Text prompt on the Korean concept “geong”—complex emotional bond unique to Korean culture.
- Response demonstrated understanding of cultural nuances and emotional depth.
- Second Test: Translations of “I love you” in various languages.
- Mixed results, generally good performance in Korean, Czech, Arabic, and others but with some inaccuracies in specific languages.
- Visual Language Tasks: Tested image text extraction using Korean text, yielding accurate results.
Conclusion
- The Hyper Cloex model shows promise in handling Korean language tasks and visual interpretation.
- Overall, it performs efficiently across various tests, indicating strong capabilities in both text and visual processing tasks.