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Wow. This was impossible days ago. Open Interpreter v0.1.2— released this morning— can setup most HuggingFace models for offline use with one command. It's local, private, and free. $ pip install --upgrade open-interpreter $ interpreter --model tiiuae/falcon-180B

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killian

32,393 subscribers

1,046,461 Aufrufe • vor 2 Jahren •via X (Twitter)

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10 Kommentare

Profilbild von Pietro Schirano
Pietro Schiranovor 2 Jahren

WHAT

Profilbild von Sven Jasper
Sven Jaspervor 2 Jahren

@readwise save thread

Profilbild von Tony Silva
Tony Silvavor 2 Jahren

am I able to run flacon-180b on a MacBook Pro M2?

Profilbild von Vinod Varma
Vinod Varmavor 2 Jahren

Do you see an API coming for this in future with the capability to setup sandbox python environment like CodeInterpreter API ?

Profilbild von hh2gk
hh2gkvor 2 Jahren

Wow - Truly amazing work!

Profilbild von Thunderhead
Thunderheadvor 2 Jahren

Woah 👀

Profilbild von AIadvocate
AIadvocatevor 2 Jahren

Incredible work, would be awesome to mashup with with #gpt4all 👀

Profilbild von killian
killianvor 2 Jahren

talked to andriy at @nomic_ai day before yesterday :)

Profilbild von Frank Martinez
Frank Martinezvor 2 Jahren

Raspberry Pi 4B?

Profilbild von Steve Metcalf
Steve Metcalfvor 2 Jahren

Dang! It’s like having a kid and it learns new tricks that impress its parents!

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Open Interpreter's new release looks great for locally running LLMs The tool lets LLMs run code (Python, Javascript, Shell, and more) locally. You can chat with Open Interpreter through a ChatGPT-like interface in your terminal by running $ interpreter after installing. Just do `pip install open-interpreter` and then just run `- interpreter --local` sets up fast, local LLMs. Congrats killian 👏
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Open Interpreter's new release looks great for locally running LLMs The tool lets LLMs run code (Python, Javascript, Shell, and more) locally. You can chat with Open Interpreter through a ChatGPT-like interface in your terminal by running $ interpreter after installing. Just do `pip install open-interpreter` and then just run `- interpreter --local` sets up fast, local LLMs. Congrats killian 👏

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