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This paper presents Quota Marketplace, a market-based dynamic pricing mechanism deployed at Google for efficient allocation of ML training accelerators across business units, achieving Pareto efficiency and max-min fairness under heterogeneous workload values.
Hugging Face’s open-source "ml-intern" agent automates the full post-training pipeline—from literature review and data cleaning to model tuning—given only a high-level prompt.