Run AI workloads on any cloud, store on Hugging Face: zero-egress storage with SkyPilot

Run AI workloads on any cloud, store on Hugging Face: zero-egress storage with SkyPilot Run AI workloads on any cloud, store on Hugging Face: zero-egress storage with SkyPilot Published July 7, 2026 Update on GitHub Upvote 35 Nikhil Jha njha guest Zhanghao Wu michaelvll skypilot-org Hope Wang hopechong skypilot-org Adrien Carreira XciD Julien Chaumond julien-c For most teams, models and datasets live in a bucket in one region of one cloud. The GPUs you can get, whether for development, training, or serving, increasingly sit on a different cloud than your data.

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• Run AI workloads on any cloud, store on Hugging Face: zero-egress storage with SkyPilot Published July 7, 2026 Update on GitHub Upvote 35 Nikhil Jha njha guest Zhanghao Wu michaelvll skypilot-org Hope Wang hopechong skypilot-org Adrien Carreira XciD Julien Chaumond julien-c For most teams, models and datasets live in a bucket in one region of one cloud.
• The GPUs you can get, whether for development, training, or serving, increasingly sit on a different cloud than your data.
• The moment those two come apart, you pay a cross-cloud transfer tax just to read your own data onto your own GPUs.
• Together with Hugging Face, we've joined the two halves: your models and datasets stay on the Hub, and SkyPilot runs the compute (dev, training, or serving) on whatever cluster has the GPUs.
• Mount a Hugging Face Bucket or any Hub repo into a SkyPilot job with one hf:// URL and the HF_TOKEN you already have, then launch it wherever capacity is.
• Hugging Face charges no egress, so reading your data onto those GPUs costs nothing, on any cloud.