AI BriefingHugging Face Introduces Chunk-Based Storage
Key point
Hugging Face is introducing Content-Defined Chunking (CDC) technology to overcome the limitations of Git LFS, improving storage and transfer efficiency.
Details
Hugging Face currently manages over 30PB of models and datasets with Git LFS, but the file-level versioning method causes inefficiency in that even small edits require re-uploading the entire file.
To solve this, Hugging Face is introducing the Content-Defined Chunking (CDC) method. CDC splits files into chunks of variable size based on the data content, rather than fixed size.
The main advantages of this method are as follows:
- Efficient updates: When a file is modified, only the changed chunks need to be uploaded, reducing transfer costs.
- Deduplication: Chunks with identical content are stored only once, optimizing storage space.
- Improved performance: According to benchmark results, compared to existing Git LFS, storage usage decreased by about 60%, and upload and download speeds improved by about 2-3x.
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