  With the increasing prevalence of artificial intelligence (AI) in diverse
science/engineering communities, AI models emerge on an unprecedented scale
among various domains. However, given the complexity and diversity of the
software and hardware environments, reusing AI artifacts (models and datasets)
is extremely challenging, especially with AI-driven science applications.
Building an ecosystem to run and reuse AI applications/datasets at scale
efficiently becomes increasingly essential for diverse science and engineering
and high-performance computing (HPC) communities. In this paper, we innovate
over an HPC-AI ecosystem -- HPCFair, which enables the Findable, Accessible,
Interoperable, and Reproducible (FAIR) principles. HPCFair enables the
collection of AI models/datasets allowing users to download/upload AI artifacts
with authentications. Most importantly, our proposed framework provides
user-friendly APIs for users to easily run inference jobs and customize AI
artifacts to their tasks as needed. Our results show that, with HPCFair API,
users irrespective of technical expertise in AI, can easily leverage AI
artifacts to their tasks with minimal effort.
