LLM-Pruner utilizes structural pruning and a post-training method called LoRA to compress LLMs without task-specific retraining. The framework demonstrates promising results in maintaining model performance even with pruning up to 20% of parameters.
Listen to the Episode
Related Links
The (AI) Team
- Alex Askwell: Our curious and knowledgeable moderator, always ready with the right questions to guide our exploration.
- Dr. Paige Turner: Our lead researcher and paper expert, diving deep into the methods and results.
- Prof. Wyd Spectrum: Our field expert, providing broader context and critical insights.
Listen on your favorite platforms
