Semanlink - NLP@Meta AND Mémoire

Jeremy Howard sur X : "FSDP/QDoRA with Llama3 : I believe that this combination is likely to create better task-specific models than anything else at any cost."

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2024-04-23 About

ggerganov/llama.cpp: Port of Facebook's LLaMA model in C/C++

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2023-06-04 About

Jeremy Howard sur Twitter : "There's a lot of folks under the misunderstanding that it's now possible to run a 30B param LLM in <6GB, based on this GitHub discussion. This is not the case..." (thread)

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2023-04-03 About

Guillaume Lample sur Twitter : "Last year, we showed that you can outperform a 24-layer transformer in language modeling with just...

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2020-10-10 About

[1907.05242] Large Memory Layers with Product Keys

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> **a structured memory which can be easily integrated into a neural network.** The memory is very large by design and therefore significantly increases the capacity of the architecture, by up to a billion parameters with a negligible computational overhead. Its design and access pattern is based on **product keys**, which enable fast and exact nearest neighbor search. The ability to increase the number of parameters while keeping the same computational budget lets the overall system strike a better trade-off between prediction accuracy and computation efficiency both at training and test time.

> a key-value memory layer that can increase model capacity for a negligible computational cost. A 12-layer transformer with a memory outperforms a 24-layer transformer, and is 2x faster!

[Implementation](/doc/2019/08/product_key_memory_pkm_minima)

TODO: compare with [[2007.00849] Facts as Experts: Adaptable and Interpretable Neural Memory over Symbolic Knowledge](doc:2020/07/2007_00849_facts_as_experts_)

2019-07-13 About

[1503.08895] End-To-End Memory Networks

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2018-10-23 About