I've just created c/Ollama!

Submitted ⁨⁨1⁩ ⁨day⁩ ago⁩ by ⁨catty@lemmy.world⁩ to ⁨selfhosted@lemmy.world⁩

I’ve just re-discovered ollama and it’s come on a long way and has made a difficult task of locally hosting your own LLM to simply installing a deb! It also works for Windows and Mac, so can help everyone.

I’d like to see Lemmy become useful for specific technical sub branches instead of trying to find the best existing community, so I created c/ollama for everyone to discuss, ask questions, and help each other out with ollama!

So, please, join, subscribe and feel free to post, ask questions, post tips / projects, and help out where you can!

Thanks!

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Comments

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brucethemoose@lemmy.world ⁨1⁩ ⁨day⁩ ago
TBH you should fold this into localllama? Or open source AI?

I have very mixed (mostly bad) feelings on ollama. In a nutshell, they’re kinda Twitter attention grabbers that give zero credit/contribution to the underlying framework (llama.cpp). It’s also a highly suboptimal way for most people to run LLMs, especially if you’re willing to tweak.

They’re… slimey. I would always recommend Kobold.cpp, tabbyAPI, ik_llama.cpp, Aphrodite, any number of backends over them. Anything but ollama.

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- TheHobbyist@lemmy.zip ⁨1⁩ ⁨day⁩ ago
  Indeed, Ollama is going a shady route. github.com/ggml-org/llama.cpp/pull/11016#issuecom…
  
  I started playing with Ramalama (the name is a mouthful) and it works great. There is one or two more steps in the setup but I’ve achieved great performance and the project is making good use of standards (OCI, jinja, unmodified llama.cpp, from what I understand).
  
  Go and check it out, they are compatible with models from HF and Ollama too.
  
  github.com/containers/ramalama
  
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- southernbeaver@lemmy.world ⁨1⁩ ⁨day⁩ ago
  What would you recommend to hook to my home assistant?
  
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  - brucethemoose@lemmy.world ⁨1⁩ ⁨day⁩ ago
    Totally depends on your hardware, and what you tend to ask it. What are you running?
    
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  - TheHobbyist@lemmy.zip ⁨1⁩ ⁨day⁩ ago
    Perhaps give Ramalama a try?
    
    github.com/containers/ramalama
    
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- tal@lemmy.today ⁨1⁩ ⁨day⁩ ago
  While I don’t think that llama.cpp is specifically a risk, I think that running generative AI software in a container is probably a good idea. It’s a rapidly-moving field with a lot of people contributing a lot of code that very quickly gets run on a lot of systems by a lot of people. There’s been malware that’s shown up in extensions for (for example) ComfyUI. And the software really doesn’t need to poke around at outside data.
  
  Also, because the software has to touch the GPU, it needs a certain amount of outside access. Containerizing that takes some extra effort.
  
  old.reddit.com/…/psa_please_secure_your_comfyui_i…
  
  ComfyUI users has been hit time and time again with malware from custom nodes or their dependencies. If you’re just using the vanilla nodes, or nodes you’ve personally developed yourself or vet yourself every update, then you’re fine. But you’re probably using custom nodes. They’re the great thing about ComfyUI, but also its great security weakness.
  
  Half a year ago the LLMVISION node was found to contain an info stealer. Just this month the ultralytics library, used in custom nodes like the Impact nodes, was compromised, and a cryptominer was shipped to thousands of users.
  
  Granted, the developers have been doing their best to try to help all involved by spreading awareness of the malware and by setting up an automated scanner to inform users if they’ve been affected, but what’s better than knowing how to get rid of the malware is not getting the malware at all.
  
  Ollama means sticking it in a Docker container, and that is, I think, a positive thing.
  
  If there were a close analog, like some software package that could take a given LLM model and run in podman or Docker or something, I think that that’d be great. But I think that putting the software in a container is probably a good move relative to running it uncontainerized.
  
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  - brucethemoose@lemmy.world ⁨1⁩ ⁨day⁩ ago
    I don’t understand.
    
    Ollama is not actually docker, right? It’s running the same llama.cpp engine, it’s just embedded inside the wrapper app, not containerized.
    
    And basically every LLM project ships a docker container. I know for a fact llama.cpp, TabbyAPI, Aphrodite, vllm and sglang do.
    
    You are 100% right about security though, in fact there’s a huge concern with compromised Python packages. This one almost got me: pytorch.org/blog/compromised-nightly-dependency/
    
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infeeeee@lemmy.zip ⁨1⁩ ⁨day⁩ ago
Instance independent link: !Ollama@lemmy.world

Share links to communities this way, so everyone can subscribe easily.

You should also post about this in !newcommunities@lemmy.world and !communitypromo@lemmy.ca for better discovery!

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- catty@lemmy.world ⁨1⁩ ⁨day⁩ ago
  Thanks will do all that!
  
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gashead76@lemmy.world ⁨1⁩ ⁨day⁩ ago
Cool! I’ll subscribe. I’ve got about a dozen projects I’d like to build with Ollama, if I’ll get the motivation and free time who knows?

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- catty@lemmy.world ⁨1⁩ ⁨day⁩ ago
  Start now! Install it, get a python environment up and running if you haven’t already, and get that first stupid project working which you work outwards from!
  
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  - gashead76@lemmy.world ⁨1⁩ ⁨day⁩ ago
    Already setup! I think the first thing I want to do is setup retrieval augmented generation. Several of my hobby ideas will require it I think. Started trying to read up on it a couple days ago and I had a serious lack of focus going on.
    
    I’ve been kind of hoping to come across a super simple way to implement it, but haven’t exactly looked much yet.
    
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otter@lemmy.ca ⁨1⁩ ⁨day⁩ ago
There is also !localllama@sh.itjust.works ;)

crossposting between the communities can help grow both

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