預測Hugging Face上開源AI模型的成長趨勢

Forecasting Open-Weight AI Model Growth on Hugging Face

February 21, 2025

作者: Kushal Raj Bhandari, Pin-Yu Chen, Jianxi Gao

cs.AI

摘要

隨著開放權重人工智慧領域的持續擴展——包括模型開發、重大投資及用戶興趣的增長——預測哪些模型最終將推動創新並塑造AI生態系統變得日益重要。基於與科學文獻引用動態的相似性，我們提出了一個框架來量化開放權重模型影響力的演變。具體而言，我們採用了Wang等人針對科學引用提出的模型，利用三個關鍵參數——即時性、持久性和相對適應性——來追蹤一個開放權重模型的微調模型累積數量。我們的研究發現表明，這種引用風格的方法能有效捕捉開放權重模型採用的多樣化軌跡，大多數模型都能很好地擬合，而異常值則揭示了使用中的獨特模式或突然躍升。

English

As the open-weight AI landscape continues to proliferate-with model development, significant investment, and user interest-it becomes increasingly important to predict which models will ultimately drive innovation and shape AI ecosystems. Building on parallels with citation dynamics in scientific literature, we propose a framework to quantify how an open-weight model's influence evolves. Specifically, we adapt the model introduced by Wang et al. for scientific citations, using three key parameters-immediacy, longevity, and relative fitness-to track the cumulative number of fine-tuned models of an open-weight model. Our findings reveal that this citation-style approach can effectively capture the diverse trajectories of open-weight model adoption, with most models fitting well and outliers indicating unique patterns or abrupt jumps in usage.