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Devstral

(mistral.ai)
701 points mfiguiere | 1 comments | | HN request time: 0s | source
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simonw ◴[] No.44053886[source]
The first number I look at these days is the file size via Ollama, which for this model is 14GB https://ollama.com/library/devstral/tags

I find that on my M2 Mac that number is a rough approximation to how much memory the model needs (usually plus about 10%) - which matters because I want to know how much RAM I will have left for running other applications.

Anything below 20GB tends not to interfere with the other stuff I'm running too much. This model looks promising!

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lis ◴[] No.44054806[source]
Yes, I agree. I've just ran the model locally and it's making a good impression. I've tested it with some ruby/rspec gotchas, which it handled nicely.

I'll give it a try with aider to test the large context as well.

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ericb ◴[] No.44055628[source]
In ollama, how do you set up the larger context, and figure out what settings to use? I've yet to find a good guide. I'm also not quite sure how I should figure out what those settings should be for each model.

There's context length, but then, how does that relate to input length and output length? Should I just make the numbers match? 32k is 32k? Any pointers?

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lis ◴[] No.44056025[source]
For aider and ollama, see: https://aider.chat/docs/llms/ollama.html

Just for ollama, see: https://github.com/ollama/ollama/blob/main/docs/faq.md#how-c...

I’m using llama.cpp though, so I can’t confirm these methods.

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1. nico ◴[] No.44056519[source]
Are you using it with aider? If so, how has your experience been?