COAP is a memory-efficient training method that reduces computational overhead without sacrificing performance.
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Updated
Mar 25, 2025 - Python
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memory-efficient-training
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AAMLA: An Autonomous Agentic Framework for Memory-Aware LLM-Aided Hardware Generation
hardware memory gpu eda computer-aided-design gpu-memory-profiler large-language-models llm parameter-efficient-fine-tuning agentic-workflow agentic-ai memory-efficient-training estimation-tool
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Updated
Nov 27, 2025 - Python
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