231a67e70b
* working * fixes * deprecate --iterable; cleanup * pretrain_multipack_buffer_size -> streaming_multipack_buffer_size * improvements * tests * remove unused * docs, examples * nit * nit * add val_set_size validation * val * nit * min * coderabbito * cleanup * nit * add depr warning, cleanup * nit * fix test, fix quarto * fix * review comments * review comments * fix
Streaming Dataset Examples
This directory contains example configurations for using Axolotl's streaming dataset functionality, which enables memory-efficient training with large datasets.
Examples
Run the following examples with e.g. axolotl train examples/streaming/sft.yaml; no
axolotl preprocess required!
Pretraining (pretrain.yaml)
Demonstrates streaming configuration for pretraining tasks using the fineweb-edu dataset with SmolLM2-135M.
- Uses
pretraining_datasetconfiguration for automatic streaming - Multipack attention control to prevent cross-attention between packed sequences
- Buffer size configuration for memory management
SFT (sft.yaml)
Shows how to use streaming for supervised fine-tuning with the Alpaca dataset.
- Explicit
streaming: trueflag for SFT datasets - Memory-efficient training on instruction datasets
- Evaluation datasets are currently not streamed
Key Configuration Options
streaming
- Enables streaming mode for standard datasets
- Automatically enabled for
pretraining_dataset
streaming_multipack_buffer_size
- Controls buffer size for sample packing (default: 10,000)
- Larger values improve packing efficiency but use more memory
- Adjust based on available memory
shuffle_merged_datasets
- Enables shuffling of streaming datasets
- Requires additional memory for shuffle buffer
sample_packing
- Packs multiple samples into single sequences
- Minimize per-step padding tokens
Performance Tips
- Download small / frequently-used datasets locally for better performance
- Larger buffer sizes improve packing efficiency