huggingface/llm_training_handbook
A technical handbook with scripts and commands for successfully training large language models, covering parallelism, throughput optimization, and training instabilities.
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This repository provides practical methodologies for LLM training engineers and operators working with distributed training across GPUs. It covers model parallelism strategies, throughput maximization techniques, tensor precision considerations, and debugging approaches for both software and hardware failures. Content is organized into categories for hyperparameters, SLURM job scheduling, and resource management, with working code examples alongside conceptual explanations.
Frequently asked
- What is huggingface/llm_training_handbook?
- A technical handbook with scripts and commands for successfully training large language models, covering parallelism, throughput optimization, and training instabilities.
- Is llm_training_handbook open source?
- Yes — huggingface/llm_training_handbook is open source, released under the CC-BY-SA-4.0 license.
- What language is llm_training_handbook written in?
- huggingface/llm_training_handbook is primarily written in Python.
- How popular is llm_training_handbook?
- huggingface/llm_training_handbook has 563 stars on GitHub.
- Where can I find llm_training_handbook?
- huggingface/llm_training_handbook is on GitHub at https://github.com/huggingface/llm_training_handbook.