

HPT
Overview :
HPT (Hyper-Pretrained Transformers) is a novel multi-modal large language model framework introduced by the HyperGAI research team. It enables the efficient and scalable training of large multi-modal foundation models, capable of understanding various input modalities including text, images, and videos. The HPT framework can be trained from scratch or efficiently fine-tuned using existing pre-trained vision encoders and/or large language models.
Target Users :
Suitable for researchers and developers working on tasks requiring processing and understanding multi-modal data, such as visual-language tasks, image analysis, and chart interpretation.
Use Cases
Researchers utilize HPT Pro for complex multi-modal task research
Developers leverage HPT Air for cost-benefit analysis and visual-language task processing
Businesses enhance their services' visual understanding and user interaction capabilities through HPT model-powered products
Features
Multi-modal understanding, including text, images, and videos
HPT Pro model surpasses larger models like GPT-4V and Gemini Pro on multiple benchmark tests
HPT Air model, as an open-source version, leads in performance among similar or smaller-sized models
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