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Show me I can save a considerable amount of time training a 70b parameter huggingface model by switching to Elixir, then we can talk about me learning a new lan
by paulluuk 3y ago
Show me I can save a considerable amount of time training a 70b parameter huggingface model by switching to Elixir, then we can talk about me learning a new language.
- josevalim 3y agoThe training costs and performance at that scale are mostly driven by hardware and I personally don't think language will make a large difference (I may be wrong). Most of the Elixir Nx efforts are on inference, especially on how you can embed and scale it using concurrent and distributed patterns (see this post/video [1]). It may not be what you are looking for but we have more folks deploying than training models, so maybe they will find incentives to give Elixir a try. :) [1]: https://news.livebook.dev/distributed2-machine-learning-notebooks-with-elixir-and-livebook---launch-week-1---day-2-1aIlaw https://news.livebook.dev/distributed2-machine-learning-note...
- sodapopcan 3y agoSeems like you didn't read even the first line as this article is directed at people already using Elixir who are currently doing ML stuff with Python.
- paulluuk 3y agoI did actually read most of the article. Did you read the section immediately after that? > Why is Python not Sufficient? It then proceeds to make a case why Python would not have enough speed or support for parallel processing, which is what I'm disputing.