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I think the hard part about that is you first have to train the model on a BUTT TON of that new language, because that's the only way they "learn" anything. They already know a lot of Python, so telling them to write restricted and sandboxed Python ("you can only call _these_ functions") is a lot easier.

But I'd be interested to see what you come up with.

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> that's the only way they "learn" anything

I think skills and other things have shown that a good bit of learning can be done on-demand, assuming good programming fundamentals and no surprise behavior. But agreed, having a large corpus at training time is important.

I have seen, given a solid lang spec to a never-before-seen lang, modern models can do a great job of writing code in it. I've done no research on ability to leverage large stdlib/ecosystem this way though.

> But I'd be interested to see what you come up with.

Under active dev at https://github.com/cretz/duralade, super POC level atm (work continues in a branch)

> you first have to train the model on a BUTT TON of that new language

Tokenization joke?

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