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Show HN: Needle: We Distilled Gemini Tool Calling into a 26M Model

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Re: Show HN: Needle: We Distilled Gemini Tool Calling into a 26M Model

#201
post #11

Suggestion: publish a live demo of the "needle playground". It's small enough that it should be pretty cheap to run this on a little VPS somewhere!

Should be quick and easy with WebGPU, too.

https://huggingface.co/spaces/shreyask/needle-playground

Re: Show HN: Needle: We Distilled Gemini Tool Calling into a 26M Model

#206
post #17

FYI, distilling Gemini is explicitly against the ToS: "You may not use the Services to develop models that compete with the Services (e.g., Gemini API or Google AI Studio). You also may not attempt to reverse engineer, extract or replicate any component of the Services, including the underlying data or models (e.g., parameter weights)."

...unless you are trying to get Google's attention for a job interview. :)

Re: Show HN: Needle: We Distilled Gemini Tool Calling into a 26M Model

#209

Earlier quoted context omitted.

Thanks to a Huggingface linked below, I tested it and im not impressed. prmopt: i need to contact my boss i will be late. Result: 20mins [{"name":"set_timer","arguments":{"time_human":"20 minutes"}}]. It didnt use the email tool and i tried 2-3 different ways of asking it.

Query: context: { "boss_email": "bigboss69420@corporatepersonhood.net", "upcoming_meetings": [{ with: "bigboss69420@corporatepersonhood.net", "time": "11:00" }] } user: i need to contact my boss i will be late, could you tell him I'll be 15 minutes late? Output: [{"name":"send_email","arguments":{"to":"bigboss69420@corporatepersonhood.net","subject":"upcoming_meetings","body":"I'll be 15 minutes late"}},{"name":"send…

Maybe it has to be fine-tuned per tool just like functiongemma

Re: Show HN: Needle: We Distilled Gemini Tool Calling into a 26M Model

#210
post #5

Hmm.. this might make it feasible to build something like a command line program where you can optionally just specify the arguments in natural language. Although I know people will object to including an extra 14 MB and the computation for "parsing" and it could be pretty bad if everyone started doing that. But it's really interesting to me that that may be possible now. You can include a fine-tuned model that under…

I wonder if it will make sense to have a central natural language parser of sorts managed by the OS that includes a model like this? So all command line programs can hook into this model at runtime, and you can have adaptors for fine-tuning etc.

Apple already have this working on iOS - as discussed in this recent post.

https://unix.foo/posts/local-ai-needs-to-be-norm/

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