perf-sequence-packing

What problem does it solve?

This Skill enables the validation and application of sequence packing techniques to improve training efficiency and long-context handling in large language models.

Core Features & Use Cases

• Enables offline packed SFT for LLM fine-tuning by configuring packed sequence specifications for stable training with extended context lengths.
• Supports in-batch packing for vision-language model fine-tuning, facilitating improved training throughput.
• Use Case: Adjust sequence lengths and packing parameters to enable longer context training or optimize memory usage during model finetuning for production environments.

Quick Start

Configure your training setup to use PackedSequenceSpecs for sequence length and packing specifications, then run the training process with these parameters to improve efficiency and handle long context sequences.