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I got into contributing to open-source (for me that was llama.cpp) at a uniquely opportune time.
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I just came back from a vacation to Japan with my wife and 10-month old.
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The MTP PR got merged into llama.cpp a few days back.
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This post about about a PR to llama.cpp which adds support to prefetch weights, overlapping compute for the current layer with the weight loading for the next layer.
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Autoresearch is all the rage, it's like people like never heard of while loop before.
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I recently needed to delete objects in a LIFO manner and employed an LLM to rubber-duck about what would be the best container.
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Note: this is a copy of the discussion here LLM inference is divided into 2 phases: prompt-processing (PP) and token-generation (TG).
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There are a lot of resources online about writing a fast GEMM, and they all get complicated really fast, and by the time you reach the tensor core section you need to keep a lot in context to understand.
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I have a git repo where I put in my life goals.
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Contributing to open-source projects is a goal of many programmers.