What is Low-Rank Adaptation (LoRA) | explained by the inventor | Matt Johnson
What is Low-Rank Adaptation (LoRA) | explained by the invento…
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Local Low-Rank Matrix Approximation
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Local Low-Rank Matrix Approximation
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Microsoft
🚀 LoRA (Low-Rank Adaptation) is one of those ideas that redefined efficiency in model fine-tuning. Instead of updating every parameter of a massive pre-trained model, LoRA injects small trainable matrices into specific layers — learning low-rank updates that approximate the full weight changes. This animation by Tom Yeh captures that process visually: You can almost see how LoRA decomposes the adaptation into a compact subspace, focusing only on the dimensions that truly matter for the new task
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🚀 LoRA (Low-Rank Adaptation) is one of those ideas that redefined effici…
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Designed for AI/ML/DS engineers/students, this course is a hands-on journey into low-rank adaptation (LoRA) techniques. Through a step-by-step series, you will fine-tune OpenAI/Whisper-Small and Facebook/mms-1b-all for Khmer speech (ASR), mastering low-rank optimization techniques suited for both research and deployment. Each video builds on the previous one, guiding you from easy concepts to deeper fine-tuning. Whisper notebook: https://huggingface.co/blog/fine-tune-whisper MMS notebook: https:
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