• @PerogiBoi@lemmy.ca
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    9210 months ago

    Also check out LLM Studio and GPT4all. Both of these let you run private ChatGPT alternatives from Hugging Face and run them off your ram and processor (can also offload to GPU).

    • @Just_Pizza_Crust@lemmy.world
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      2610 months ago

      I’d also recommend Oobabooga if you’re already familiar with Automatic1111 for Stable diffusion. I have found being able to write the first part of the bots response gets much better results and seems to make up false info much less.

        • Turun
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          310 months ago

          And llama file, which is a chat bot in a single executable file.

      • @EarMaster@lemmy.world
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        810 months ago

        I feel like you’re all making these names up…but they were probably suggested by a LLM all together…

    • tubbadu
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      1010 months ago

      Are they as good as chatgpt?

      • @PerogiBoi@lemmy.ca
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        10 months ago

        Mistral is thought to be almost as good. I’ve used the latest version of mistral and found it more or less identical in quality of output.

        It’s not as fast though as I am running it off of 16gb of ram and an old GTX 1060 card.

        If you use LLM Studio I’d say it’s actually better because you can give it a pre-prompt so that all of its answers are within predefined guardrails (ex: you are glorb the cheese pirate and you have a passion for mink fur coats).

        There’s also the benefit of being able to load in uncensored models if you would like questionable content created (erotica, sketchy instructions on how to synthesize crystal meth, etc).

      • @Hestia@lemmy.world
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        110 months ago

        Depends on your use case. If you want uncensored output then running locally is about the only game in town.

    • @webghost0101@sopuli.xyz
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      710 months ago

      Something i am really missing is a breakdown of How good these models actually are compared to eachother.

      A demo on hugging face couldnt tell me the boiling point of water while the authors own example prompt asked the boiling point for some chemical.

    • @M500@lemmy.ml
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      510 months ago

      I can’t find a way to run any of these on my homeserver and access it over http. It looks like it is possible but you need a gui to install it in the first place.

        • @Scipitie@lemmy.dbzer0.com
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          10 months ago

          (edit: here was wrong information - I apologize to the OP!)

          Plus a GUI install is not exactly the best for reproducability which at least I aim for with my server infrastructure.

          • @Emma_Gold_Man@lemmy.dbzer0.com
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            210 months ago

            You don’t need to run an X server on the headless server. As long as the libraries are compiled in to the client software (the GUI app), it will work. No GUI would need to be installed on the headless server, and the libraries are present in any common Linux distro already (and support would be compiled into a GUI-only app unless it was Wayland-only).

            I agree that a GUI-only installer is a bad thing, but the parent was saying they didn’t know how it could be done. “ssh -X” (or -Y) is how.

            • @Scipitie@lemmy.dbzer0.com
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              210 months ago

              That’s a huge today-I-learned for me, thank you! I took ill throw xeyes on it just to use ssh - C for the first time in my life. I actually assumed wrong.

              I’ll edit my post accordingly!

  • stevedidWHAT
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    7910 months ago

    Open source good, together monkey strong 💪🏻

    Build cool village with other frens, make new things, celebrate as village

    • @Zeon@lemmy.world
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      10 months ago

      It’s free / libre software, which is even better, because it gives you more freedom than just ‘open-source’ software. Make sure to check the licenses of software that you use. Anything based on GPL, MIT, or Apache 2.0 are Free Software licenses. Anyways, together monkey strong 💪

  • WetFerret
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    1010 months ago

    I would also reccommend faraday.dev as a way to try out different models locally using either CPU or GPU. I believe they have a build for every desktop OS.

  • @randon31415@lemmy.world
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    810 months ago

    I have recently been playing with llamafiles, particularly Llava which, as far as I know, is the first multimodal open source llm (others might exist, this is just the first one I have seen). I was having it look at pictures of prospective houses I want to buy and asking it if it sees anything wrong with the house.

    The only problem I ran into is that window 10 cmd doesn’t like the sed command, and I don’t know of an alternative.

  • ElPussyKangaroo
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    510 months ago

    Any recommendations from the community for models? I use ChatGPT for light work like touching up a draft I wrote, etc. I also use it for data related tasks like reorganization, identification etc.

    Which model would be appropriate?

  • tubbadu
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    10 months ago

    Is it as good as chatgpt?

    • Infiltrated_ad8271
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      1210 months ago

      The question is quickly answered as none is currently that good, open or not.

      Anyway it seems that this is just a manager. I see some competitors available that I have heard good things about, like mistral.

    • @Falcon@lemmy.world
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      10 months ago

      Many are close!

      In terms of usability though, they are better.

      For example, ask GPT4 for an example of cross site scripting in flask and you’ll have an ethics discussion. Grab an uncensored model off HuggingFace you’re off to the races

      • tubbadu
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        110 months ago

        Seems interesting! Do I need high end hardware or can I run them on my old laptop that I use as home server?

        • @Falcon@lemmy.world
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          110 months ago

          Oh no you need a 3060 at least :(

          Requires cuda. They’re essentially large mathematical equations that solve the probability of the next word.

          The equations are derived by trying different combinations of values until one works well. (This is the learning in machine learning). The trick is changing the numbers in a way that gets better each time (see e.g. gradient descent)