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remilouf commented on .txt raises $11.9M to make language models programmable   techcrunch.com/2024/10/17... · Posted by u/cpfiffer
jart · a year ago
The llama.cpp --grammar flag just raised $12m from European investors.
remilouf · a year ago
This is actually pretty funny.
remilouf commented on Show HN: Infinite Testimonials with FastHTML, Outlines, and Modal   github.com/aastroza/fasth... · Posted by u/cpfiffer
zero-sharp · 2 years ago
So it's a bullshit generator? Hopefully this is just for demos.
remilouf · 2 years ago
That’d be a pretty inefficient way to generate bullshit at scale
remilouf commented on     · Posted by u/remilouf
remilouf · 2 years ago
LLM evaluations are very sensitive to the details of the prompt's structure. This post shows how using structured generation reduces the results' variance and the ranking shifts.
remilouf commented on Tool Use (function calling)   docs.anthropic.com/claude... · Posted by u/akadeb
rolisz · 2 years ago
my concern with grammar based sampling is that it makes the model dumber: after all, you are forcing it to say something else than what it thought would be best.
remilouf · 2 years ago
Looks like it’s quite the opposite: http://blog.dottxt.co/performance-gsm8k.html
remilouf commented on Structured Generation Improves LLM Performance: GSM8K Benchmark   blog.dottxt.co/performanc... · Posted by u/Homunculiheaded
curionav · 2 years ago
Intuitively, regex or json grammar have a much lower "semantic dimension" than what today LLMs allow. Maybe the observed performance gains result from such lower dimensionality.
remilouf · 2 years ago
What do you mean by "semantic dimension"?
remilouf commented on Structured Generation Improves LLM Performance: GSM8K Benchmark   blog.dottxt.co/performanc... · Posted by u/Homunculiheaded
remilouf · 2 years ago
That whole structured generation line of work looks promising. I hope someone else takes this and runs evaluations on other benchmarks. Curious to see if the results translate!

u/remilouf

KarmaCake day436May 14, 2017
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Twitter: @remilouf GH: https://github.com/rlouf
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