MatMul Free Language Modeling: New Ways of LLM Training & Inference
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- Опубліковано 19 лип 2024
- In this tutorial, I dive deep into the world of scalable MatMul-free language modeling. You'll learn about the basics of matrix multiplication (MatMul), its role in neural networks and large language models, and the challenges it presents. Discover how MatMul-free language models operate, leveraging BitLinear layers with ternary weights to achieve impressive efficiency and performance.
I'll also explore the GPU-efficient implementation that reduces memory usage by up to 61% during training and significantly improves inference speed, as well as the custom FPGA hardware solution designed for brain-like efficiency.
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I was hoping for a more in depth description of the architecture. For example, I looked at the paper and I understand the equations on pg. 6 and 7. However, I do not understand how they connected to each other : they even use the same symbol gt as....an output in both cases.
the link on description isn’t working