ShinoharaHare/LLM-Training
A distributed training framework for large language models powered by Lightning.
This framework helps machine learning practitioners efficiently train large language models for various tasks like pre-training, instruction tuning, or alignment methods such as DPO and ORPO. You provide raw text data and configuration settings, and it outputs a trained language model ready for deployment or further fine-tuning. It's designed for ML engineers or researchers working with large-scale text generation and understanding models.
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Use this if you need to train or fine-tune large, GPT-like text models on large datasets across multiple machines, requiring advanced distributed training features like tensor parallelism or data packing.
Not ideal if you are working with non-text models, or if you prefer a simpler, less customizable solution for smaller models or single-GPU training.
Stars
24
Forks
4
Language
Python
License
Apache-2.0
Category
Last pushed
Jul 31, 2025
Commits (30d)
0
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