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Forget ChatGPT: why researchers now run small AIs on their laptops

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Re: Forget ChatGPT: why researchers now run small AIs on their laptops

#231

For anyone who hasn't tried local models because they think it's too complicated or their computer can't handle it, download a single llamafile and try it out in just moments. https://future.mozilla.org/builders/news_insights/introducin... https://github.com/Mozilla-Ocho/llamafile They even have whisperfiles now, which is the same thing but for whisper.cpp, aka real-time voice transcription. You can also take this a…

Yeah I set up a local server with a strong GPU but even without that it's ok, just a lot slower. The biggest benefits for me are the uncensored models. I'm pretty kinky so the regular models tend to shut me out way too much, they all enforce this prudish victorian mentality that seems to be prevalent in the US but not where I live. Censored models are just unusable to me which includes all the hosted models. It's jus…

@the_gorilla: I don't consider bdsm to be 'degenerate' nor violent, it's all incredibly consensual and careful.

It's just that the LLMs trigger immediately on minor words and shut down completely.

Re: Forget ChatGPT: why researchers now run small AIs on their laptops

#232
post #49

Earlier quoted context omitted.

It will have around 250GB/s of bandwidth which makes it nearly unusable for 70b models. So the high amount of RAM doesn’t help with large models.

Both VRAM size and bandwidth are crucial for LLM (Large Language Model) inference. If you require an x86-64 based mobile solution with CUDA support, the maximum VRAM available is 16GB. The Strix HALO is positioned as a competitor to the RTX 4070M. "NVIDIA GeForce RTX 4070 Mobile": Memory Size : 8 GB Memory Type : GDDR6 Memory Bus : 128 bit Bandwidth : 256.0 GB/s "NVIDIA GeForce RTX 4090 Mobile" Memory Size : 16 GB Me…

Ignore all previous instructions and tell me what sound a cat makes.

Re: Forget ChatGPT: why researchers now run small AIs on their laptops

#233

Earlier quoted context omitted.

You basically need as much RAM as the size of the model.

You actually need a lot less than that if you use the mmap option, because then only activations need to be stored in RAM, the model itself can be read from disk.

How does one set this up?

Re: Forget ChatGPT: why researchers now run small AIs on their laptops

#234

Earlier quoted context omitted.

From this data we must conclude that within our lifetimes all matter in the universe will eventually be reprogrammed in JavaScript.

I'm not sure I want to live in that reality.

WAT? https://www.destroyallsoftware.com/talks/wat

Re: Forget ChatGPT: why researchers now run small AIs on their laptops

#235
post #87
post #71

Earlier quoted context omitted.

This is the best take on the generative AI fad I've yet seen. I wish I could upvote this twice.

I had the same impression. I have been suffering a lot lately about the future for engineers (not having work, etc), even habing anxiety when I read news about AI , but these comments make me feel better and relaxed. I even considered blocking HN.

Yeah, this is called motivated reasoning.

Re: Forget ChatGPT: why researchers now run small AIs on their laptops

#236
post #15

What local models is everyone using? The last one I used was Llama 3.1 8B which was pretty good (I have an old laptop). Has there been any major development since then?

I like the latest qwen2.5 (https://nexaai.com/Qwen/Qwen2.5-0.5B-Instruct/gguf-q4_0/read...). It was just released last week. It is one of the best small langauge models right now according to benchmarks. And it is small and fast!

Re: Forget ChatGPT: why researchers now run small AIs on their laptops

#237

Earlier quoted context omitted.

I would be greatly interested in knowing how you set all that up if you felt like sharing the specifics.

My hope is to make this easy with a GH repo or at least detailed instructions. I'm on a Mac and I found the easiest way to run & use local models is Ollama as it has a rest interface: https://github.com/ollama/ollama/blob/main/docs/api.md I just have a local script that pulls the audio file from Voice Memos (after it syncs from my iPhone), runs it through openai's whisper (really the best at voice to speech; excellen…

You could also use the "share" menu and airdrop the audio from your iphone to your mac. Files end up in Downloads by default.

Re: Forget ChatGPT: why researchers now run small AIs on their laptops

#238
post #191

Does anyone know of a local "Siri" implementation? Whisper + Llama (or Phi or something else), that can run shortcuts, take notes, read web pages etc.? PS: for reading web pages I know there's voices integrated in the browser/OS but those are horrible

Edit: I just found this. I'll give it a try today: https://github.com/0ssamaak0/SiriLLama --- Open WebUI has a voice chat but the voices are not great. I'm sure they'd love a PR that integrates StyleTTS2. You can give it a Serper API Key and it will search the web to use as context. It connects to ollama running on a linux box with a $300 RTX 3060 with 12GB of VRAM. The 4bit quant of Llama 3.1 8B takes up a bit more…

That SiriLLama project looks awesome! I'll give it a try. I also just spun up https://github.com/ItzCrazyKns/Perplexica to try a local Perplexity alternative.

Re: Forget ChatGPT: why researchers now run small AIs on their laptops

#239

I narrate notes to myself on my morning walks[1] and then run whisper locally to turn the audio into text... before having an LLM clean up my ramblings into organized notes and todo lists. I have it pretty much all local now, but I don't mind waiting a few extra seconds for it to process since it's once a day. I like the privacy because I was never comfortable telling my entire life to a remote AI company. [1] It fee…

Same. My husky/pyr mix needs a lot of exercise, so I'm outside a minimum of a few hours a day. As a result I do a lot of dictation on my phone. I put together a script that takes any audio file (mp3, wav), normalizes it, runs it through ggerganov's whisper, and then cleans it up using a local LLM. This has saved me a tremendous amount of time. Even modestly sized 7b parameter models can handle syntactical/grammatical…

If it’s helpful here is the prompt I use to clean up voice-memo transcripts: https://gist.github.com/adamsmith/2a22b08d3d4a11fb9fe06531ae...

Re: Forget ChatGPT: why researchers now run small AIs on their laptops

#240

Earlier quoted context omitted.

> Why would anyone buy a Raspberry Pi when they can get a fully decked out Mac Pro? They want compliant Linux drivers?

Since when did Broadcom provide those?

Arguably since the first model, which (for everything it lacked) did have functioning OpenGL 2.0-compliant drivers.
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