Great to see @CommonCrawl using and recommending @huggingface Buckets for large constantly evolving ...
TL;DR · AI Summary
Hugging Face CEO Clement Delangue announced that CommonCrawl is using and recommending Hugging Face Buckets for handling large constantly evolving training datasets, which is suitable for private model and dataset management.
Key Takeaways
- CommonCrawl is using Hugging Face Buckets to handle large continuously evolving
- Hugging Face Buckets supports storage management of private models and datasets
- The service is specifically designed for version control and distribution needs
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Hugging Face CEO announces that their object storage service Buckets is being used by CommonCrawl for processing large constantly evolving training datasets.
Hugging Face Buckets is particularly suitable for organizations with private models or datasets for data management.
The Hugging Face team encourages users to try the Buckets service and provide usage feedback.
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- Hugging Face Buckets数据集管理
- CommonCrawl采用
- 大规模训练数据集
- 私有模型支持
- 数据集管理
- 持续演进数据
- 版本控制
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CommonCrawl is using and recommending Hugging Face Buckets for handling large constantly evolving training datasets
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clem 
Great to see
using and recommending
Buckets for large constantly evolving training datasets! If you have private models or datasets, try it and let us know what you think about it! huggingface.co/storage
