Load media from S3 and other cloud storage
Import images, videos, and audio files from S3, GCS, HTTP URLs, or local paths into Pixeltable tables.
Load datasets from Hugging Face Hub into Pixeltable tables for processing with AI models.
Data Import/Export · Notebook · Updated
Colab runs it in your browser. If it calls a model provider, it asks for that provider's API key in a cell.
You use pxt.create_table() with a Hugging Face dataset as the source parameter. Pixeltable automatically maps HF types to Pixeltable column types.
pip install pixeltable datasets
pxt.create_table()add_computed_column()# Import each split separately for claritytrain_data = pxt.create_table('hf_demo/reviews_train', source=hf_dataset_dict['train'])test_data = pxt.create_table('hf_demo/reviews_test', source=hf_dataset_dict['test'])
One cell of the notebook, copied as it is. Open it in Colab for the rest.
Import images, videos, and audio files from S3, GCS, HTTP URLs, or local paths into Pixeltable tables.
When Pixeltable generates media files (thumbnails, extracted frames, processed images), by default it stores them locally.
Convert Pixeltable data to PyTorch DataLoader format for model training.
Send and receive data from PostgreSQL, SQLite, MySQL, TigerData, or Snowflake for use in external applications.