this post was submitted on 12 Oct 2024
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Selfhosted

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A place to share alternatives to popular online services that can be self-hosted without giving up privacy or locking you into a service you don't control.

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Instructions here: https://github.com/ghobs91/Self-GPT

If you’ve ever wanted a ChatGPT-style assistant but fully self-hosted and open source, Self-GPT is a handy script that bundles Open WebUI (chat interface front end) with Ollama (LLM backend).

  • Privacy & Control: Unlike ChatGPT, everything runs locally, so your data stays with you—great for those concerned about data privacy.
  • Cost: Once set up, self-hosting avoids monthly subscription fees. You’ll need decent hardware (ideally a GPU), but there’s a range of model sizes to fit different setups.
  • Flexibility: Open WebUI and Ollama support multiple models and let you switch between them easily, so you’re not locked into one provider.
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[–] [email protected] 22 points 1 month ago (25 children)

whats great is that with ollama and webui, you can as easily run it all on one computer locally using the open-webui pip package or in a remote server using the container version of open-webui.

Ive run both and the webui is really well done. It offers a number of advanced options, like the system prompt but also memory features, documents for RAG and even a built in python ide for when you want to execute python functions. You can even enable web browsing for your model.

I'm personally very pleased with open-webui and ollama and they both work wonders together. Hoghly recommend it! And the latest llama3.1 (in 8 and 70B variants) and llama3.2 (in 1 and 3B variants) work very well, even on CPU only, for the latter! Give it a shot, it is so easy to set up :)

[–] [email protected] 1 points 1 month ago (4 children)

What are your PC specifications for running Ollama3.1:70B smoothly?

[–] [email protected] 0 points 1 month ago (3 children)

I wish I could. I have an RTX 3060 12GB, I run mostly llama3.1 8B versions in fp8, at 30-35 tokens/s.

[–] [email protected] 1 points 1 month ago (2 children)

I can confirm that it does not run (at least not smoothly) with an Nvidia 4080 12Gb. However, gemma2:27B runs pretty well. Do you think if we add another graphical card, a modest one, maybe the llama3.1:70B could run?

[–] [email protected] 1 points 1 month ago

I have no idea if ollama can handle multi-GPU. The 70B in it's q2_k quantized form requires already 26GB of memory, so you would need at least that to run it well and that would only imply it could be entirely run on GPU, which is the best case scenario, but not at what speed.

I know some people with apple silicon who have enough memory to run the 70B model and for them it runs fast enough to be usable. You may be able to find more info about it online.

[–] [email protected] 1 points 1 month ago* (last edited 1 month ago)

No, but you can run Qwen 2.5 34B with 24GB total.

Host it in TabbyAPI instead of ollama too. Use its native tensor parallelism and Q4 cache, it will fly.

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