Scaling AI-Based Data Processing with Hugging Face + Dask
The Hugging Face platform has many datasets and pre-trained models that make using and training state-of-the-art machine learning models increasingly accessible. However, it can be hard to scale AI tasks because AI datasets are often large (100s GBs to TBs) and using Hugging Face transformers for model inference can sometimes be computationally expensive.
Dask, a Python library for distributed computing, can handle out-of-core computing (processing data that doesn’t fit in memory) by breaking datasets into manageable chunks. This makes it easy to do things like:
- Efficient data loading and preprocessing of TB-scale datasets with an easy to