"Open source AI is the path forward," says Mark Zuckerberg, misusing the term.
    • chiisana@lemmy.chiisana.netEnglish
      21·
      2 months ago

      What’s the resources requirements for the 405B model? I did some digging but couldn’t find any documentation during my cursory search.

      • modeler@lemmy.worldEnglish
        36·
        2 months ago

        Typically you need about 1GB graphics RAM for each billion parameters (i.e. one byte per parameter). This is a 405B parameter model. Ouch.

        Edit: you can try quantizing it. This reduces the amount of memory required per parameter to 4 bits, 2 bits or even 1 bit. As you reduce the size, the performance of the model can suffer. So in the extreme case you might be able to run this in under 64GB of graphics RAM.

        • cheddar@programming.devEnglish
          111·
          2 months ago

          Typically you need about 1GB graphics RAM for each billion parameters (i.e. one byte per parameter). This is a 405B parameter model.

        • Siegfried@lemmy.worldEnglish
          6·
          2 months ago

          At work we habe a small cluster totalling around 4TB of RAM

          It has 4 cooling units, a m3 of PSUs and it must take something like 30 m2 of space

        • 1984@lemmy.todayEnglish
          3·
          2 months ago

          Can you run this in a distributed manner, like with kubernetes and lots of smaller machines?

      • sunzu@kbin.run
        10·
        2 months ago

        405b ain’t running local unless you got a proepr set up is enterpise grade lol

        I think 70b is possible but I haven’t find anyone confirming it yet

        Also would like to know specs on whoever did it

          • sunzu@kbin.run
            3·
            2 months ago

            I gonna add some RAM with hope I can split original 70b between GPU and RAM. 8b is great what it is as is

            Looks like it should be possible, not sure how much performance hit offloading to RAM will do. Fafo

          • bizarroland@fedia.io
            3·
            2 months ago

            I have a home server with 140 gigs of RAM, it was surprisingly cheap. It’s an HP z6 with the 6146 gold xeon processor.

            I found a seller who was selling it with a low spec silver and 16 gigs of RAM for like 250 bucks.

            Found the processor upgrade for about $120 and spend another $150 on 128gb of second-hand ECC ddr4.

            I think the total cost was something like $700 after throwing a couple of 8 TB hard drives in.

            I’ve also placed a Nvidia 4070 in it, which I got doing some horse trading.

            How close am I on the specs to being able to run the 70b version?

        • raldone01@lemmy.worldEnglish
          31·
          2 months ago

          I regularly run llama3 70b unqantesized on two P40s and CPU at like 7tokens/s. It’s usable but not very fast.

            • raldone01@lemmy.worldEnglish
              2·
              2 months ago

              My specs because you asked:

              CPU: Intel(R) Xeon(R) E5-2699 v3 (72) @ 3.60 GHz
GPU 1: NVIDIA Tesla P40 [Discrete]
GPU 2: NVIDIA Tesla P40 [Discrete]
GPU 3: Matrox Electronics Systems Ltd. MGA G200EH
Memory: 66.75 GiB / 251.75 GiB (27%)
Swap: 75.50 MiB / 40.00 GiB (0%)
                • raldone01@lemmy.worldEnglish
                  2·
                  2 months ago

                  Each card has 24GB so 48GB vram total. I use ollama it fills whatever vrams is available on both cards and runs the rest on the CPU cores.

            • raldone01@lemmy.worldEnglish
              1·
              2 months ago

              What are you asking exactly?

              What do you want to run? I assume you have a 24GB GPU and 64GB host RAM?

      • Blaster M@lemmy.worldEnglish
        6·
        2 months ago

        As a general rule of thumb, you need about 1 GB per 1B parameters, so you’re looking at about 405 GB for the full size of the model.

        Quantization can compress it down to 1/2 or 1/4 that, but “makes it stupider” as a result.

    • bitfucker@programming.devEnglish
      1·
      2 months ago

      So does OSM data. Everyone can download the whole earth but to serve it and provide routing/path planning at scale takes a whole other skill and resources. It’s a good thing that they are willing to open source their model in the first place.

  • abcdqfr@lemmy.worldEnglish
    226·
    2 months ago

    Wake me up when it works offline “The Llama 3.1 models are available for download through Meta’s own website and on Hugging Face. They both require providing contact information and agreeing to a license and an acceptable use policy, which means that Meta can technically legally pull the rug out from under your use of Llama 3.1 or its outputs at any time.”

  • hperrin@lemmy.worldEnglish
    141·
    2 months ago

    Yo this is big. In both that it is momentous, and holy shit that’s a lot of parameters. How many GB is this model?? I’d be able to run it if I had an few extra $10k bills lying around to buy the required hardware.

  • i_am_a_cardboard_box@lemmy.worldEnglish
    5·
    2 months ago

    Kind of petty from Zuck not to roll it out in Europe due to the digital services act… But also kind of weird since it’s open source? What’s stopping anyone from downloading the model and creating a web ui for Europe users?

  • sunzu@kbin.run
    31·
    2 months ago

    Did anyone get 70b to run locally?

    If so what, what hardware specs?