TRBoom

Co-op with my brothers and dad (who was a scuba trainer) is gonna be a blast.

I have a general unease about the sea and water in general so I’m sure it’ll have some lovely tense moments once we get playing.

I love how the url slug for that article seems to imply that it’s about openai stopping shootings.

Yup! If you installed the os on it.

So you have one usb with the iso flashed to it and a second to install the os on. Use the first to install to the second.

So I trick for the double drives is to pop in a low profile usb drive and install the os on that. Then you can use the ssd/hdd for other things.

I think he wants a toll too. He’s just jealous of the money.

I certainly hadn’t heard any rumors until now.

Good response. Love it when peeps own up to their mistskes.

100% agree. At this point I am assuming everything sent through their servers is actively being collected for LLM training.

Unless someone has released something new while I haven’t been paying attention, all the gen AIs are essentially frozen. Your use of them can’t impact the actual weights inside of the model.

If it seems like it’s remember things is because of the actual input of the LLM is larger than the input you will usually give it.

For instance lets say the max input for a particular LLM is 9096 tokens. The first part of that will be instructions from the owners of the LLM to prevent their model from being used for things they don’t like. Lets say the first 2000 tokens. That leaves 7k or so for a conversation that will be ‘remembered’.

Now if someone was really savvy, they’d have the model generate summaries of the conversation and stick them into another chunk of memory, maybe another 2000 tokens worth, that way it will seem to remember more than just the current thread. That would leave you with 5000 tokens to have a running conversation.

Here’s mine, no judging for how I set the ip

name: jellyfin
services:
    jellyfin:
        container_name: jellyfin.live
        networks:
            mynet:
                ipv4_address: 192.168.5.3
        ports:
            - 8096:8096
        volumes:
            - jellyfin-config:/config
            - jellyfin-cache:/cache
            - type: bind
              source: /mnt
              target: /Media Disk 1
            - type: bind
              source: /mnt
              target: /Media Disk 2
            - type: bind
              source: /mnt
              target: /Media Disk 3
        environment:
            - HEALTHCHECK_URL=192.168.5.3
        restart: unless-stopped
        deploy:
            resources:
                reservations:
                    devices:
                        - driver: nvidia
                          count: all
                          capabilities:
                              - gpu
        image: jellyfin/jellyfin:latest
networks:
    mynet:
        external: true
        name: mynet
volumes:
    jellyfin-config:
        external: true
        name: jellyfin-config
    jellyfin-cache:
        external: true
        name: jellyfin-cache

The section on the GPU looks like yours. I had to do something to get it working, but it’s been forever.

Budget-Chicken-2425

Looks like his account is suspended now.