HighCapability
Hugging Face Introduces Storage Buckets for ML Artifacts
Action Required
Teams can now efficiently manage the constantly evolving data streams of ML workflows, reducing storage costs and improving pipeline performance.
AI Impact Summary
Hugging Face is introducing Storage Buckets, a new object storage solution built on Xet, to handle the constantly changing intermediate files generated by modern ML workflows. This addresses the limitations of Git for managing these mutable artifacts, offering faster transfers, efficient deduplication, and a more streamlined workflow for training pipelines and data processing. Users can now programmatically manage these buckets via CLI or Python, integrating seamlessly with existing Hugging Face tools and libraries.
Hugging Face Introduces Storage Buckets for ML Artifacts
Affected Systems
Hugging Face Hub
- Date
- Date not specified
- Change type
- capability
- Severity
- high