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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...

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Rohan Paul

150,800 subscribers

154,611 просмотров • 2 лет назад •via X (Twitter)

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Комментарии: 7

Фото профиля Mike Bird (Hiring)
Mike Bird (Hiring)2 лет назад

We strive to be the most powerful, capable local option for benefiting from LLMs!

Фото профиля Sanim Hassan 🇮🇳
Sanim Hassan 🇮🇳2 лет назад

What are the hardware requirements for using this?

Фото профиля Aritra Roy Gosthipaty
Aritra Roy Gosthipaty2 лет назад

The keras team is going to like this! CC: @martin_gorner @fchollet

Фото профиля Matthew Zeits
Matthew Zeits2 лет назад

NVM interpreter --api_base " --api_key "fake_key"

Фото профиля Andrii 🌄 Syrokomskyi
Andrii 🌄 Syrokomskyi1 год назад

So many posts about "deploying LLM locally"... I like "locally", really. But just not LLM. It's interesting, but not practical… for my laptop)

Фото профиля Sinh Nguyen
Sinh Nguyen2 лет назад

No hesitation?

Фото профиля Matthew Zeits
Matthew Zeits2 лет назад

What if my instance of ollama is running on another machine?

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Today I’m launching Open Interpreter, an open-source Code Interpreter that runs locally. Summarize PDFs, visualize datasets, and control your browser — all from a ChatGPT-like interface in your terminal. ● $ pip install open-interpreter $ interpreter
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Open Interpreter is like ChatGPT Code Interpreter, but you can run it locally on your computer, and it is 100% open-source. Write and execute code, analyze data, control your computer, and more. Great work killian Here's how to install and use it: 👇
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Open Interpreter is like ChatGPT Code Interpreter, but you can run it locally on your computer, and it is 100% open-source. Write and execute code, analyze data, control your computer, and more. Great work killian Here's how to install and use it: 👇

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