falken, to ai
@falken@qoto.org avatar

I open sourced a thing !

A super simple web GUI for @mozilla 's

Should pass the SO test.

https://codeberg.org/falken/simple-gpt

stlhood, to random

New blog post! : four months of progress towards democratizing AI: https://future.mozilla.org/news/llamafile-four-months-of-progress-towards-democratizing-ai/

governa, to random
@governa@fosstodon.org avatar

0.7 Brings AVX-512 Support: 10x Faster Prompt Eval Times For AMD Zen 4

https://www.phoronix.com/news/Llamafile-0.7

itnewsbot, to ArtificialIntelligence

A Straightforward AI Voice Assistant, On a Pi - With AI being all the rage at the moment it’s been somewhat annoying that using a ... - https://hackaday.com/2024/02/20/a-straightforward-ai-voice-assistant-on-a-pi/

ErikJonker, to llm
@ErikJonker@mastodon.social avatar

Playing around with small LLM's on my very old laptop using Llamafile , all those models are totally unreliable, hallucinate a lot. Not surprising if you think about how relatively small they are, my resources etc. This is fun to play around with and you can easily change the settings use another model etc. As a learning experience great, for practical use i will stick with ChatGPT4 .
https://github.com/Mozilla-Ocho/llamafile

kjr,
@kjr@babka.social avatar

@ErikJonker hello,
In your experiment did you test Mistral-7B-Instruct and Mixtral-8x7B-Instruct?

ErikJonker, to llm
@ErikJonker@mastodon.social avatar

Nog nooit echt plezier gehad van glasvezel met Gigabit snelheid maar nu wel fijn met het downloaden van Mixtral-8x7B-Instruct , 30 GB 😆
https://github.com/Mozilla-Ocho/llamafile

cbontenbal,
@cbontenbal@mastodon.social avatar

@ErikJonker En dan heb je dus een LLM lokaal draaien. Moet die nog getraind worden met data?

ErikJonker,
@ErikJonker@mastodon.social avatar

@cbontenbal Nee, die is dan al getraind

ErikJonker, (edited ) to ai
@ErikJonker@mastodon.social avatar

Amazing, with everybody can experiment with a large language model on their own computer, it's maybe not up to the level of GPT4 but still amazing, running on local resources. My laptop is four years old 🙂
https://github.com/Mozilla-Ocho/llamafile

happyborg, to llm
@happyborg@fosstodon.org avatar

Try a local using 's :

  1. Get the 4.3GB file:
    curl -LO https://huggingface.co/jartine/llava-v1.5-7B-GGUF/resolve/main/llava-v1.5-7b-q4-server.llamafile

  2. Make executable

  3. Run it

  4. Visit http://127.0.0.1:8080/

You're welcome!

This is a text and image capable LLM, so ~ 4

h/t @simon

More in Simon's blog: https://simonwillison.net/2023/Nov/29/llamafile/

happyborg,
@happyborg@fosstodon.org avatar

@simon
Has anyone found a use for (see above)?

Serious question. It's interesting to play with but I haven't found anything I'd use it for yet. The only thing it seems it may be good at is summarising a news page and articles filtered by subject - though I'm not sure that's really useful to me.

heysupratim,

@happyborg @simon The mental model with decently large models (>7b params ) is you have to treat them as just nicer thought assistants.

Basically an improved focused search and text generator.

Anytime you require generation of some volume of textual data, just use your LLM as a take off point

devinprater, to ai

Well, I'm sure an NVDA addon with this will be here soon. Just amazing how far things have come. I mean, I hope there's a Windows version of the Llava part of this anyway.

llamafile is the new best way to run a LLM on your own computer:

https://simonwillison.net/2023/Nov/29/llamafile/

pax,

@devinprater but where I can download the bigger model from? the hugging face interface is quite bad.

devinprater,

@pax I'm not sure

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