this post was submitted on 08 Feb 2024
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Huh, thanks to this kick-ass comment, I'm now running some different llama models locally on my machine.
For those wondering, all of them that I've tried (llama2, llama2-uncensored, and mistral) all respond really quickly and the text comes faster than I can read. Quicker wouldn't seem to be of any use for me so I'm happy.
Specs:
Works fine on Windows though WSL 2 on Ubuntu 22.04.
Yeah, some of the smaller models are even reasonable on my old laptop in CPU mode.
General rule of thumb: The larger the model, the better it is. But not necessarily. 😉 I've found
zephyr
andmistral
are both quite good for a tradeoff and work on CPU. Of the ones that really need more RAM and/or a GPU with a lot of vRAM,mixtral
seems like the best.Additional fun is to use a
Modalfile
(which is like aContainerfile
, but is a recipe for models instead of containers) to customize a local model on top of one of the existing ones.For a simple one to demonstrate, I have a system instruction to output everything in the form of the poem "This Is Just To Say", but customized per topic.
It really works best with
mixtral
(I've tried other ones, especially smaller ones):Yes, you just instruct the system with natural text like that and it (usually) abides. I tried it without the poem being referenced inline, and it mostly worked fine... but it works even better being mentioned in the file.
I have that saved in
~/Projects/ollama/
asModelfile.fun-plums
I run the server almost as above, but now also pass in my ollama project directory as a mounted volume with
z
(for SELinux mapping)... don't forget to have runsudo setsebool container_use_devices=true
first, else it won't work:(You can run this command if you already have the server running. It will replace it with the new one. This is for AMD. You'd want to use the NVidia or CPU container if you don't have an AMD card. The CPU container is the fasted to download. The version here is newer than the one for AMD that I listed above, so it might be a multi-gigabyte download if you don't have this new one yet. The important and new part is
~/Projects/ollama:/models:z
)Then, create the model. This will be almost instant if you already have the base model downloaded (in this case,
mixtral
), otherwise it will auto-download the base model:(The path to the model in this command is the internal path from the point of view within the container.)
Then, you run it like any other model.
Here's me running it, and bringing up the topic of leftover pizza.
You can also paste the text from the reader mode of an article and it'll summarize it with a poem based on that one. 🤣
For example, copying and pasting the text from https://www.theverge.com/2024/2/10/24068931/star-wars-phantom-menace-theater-showings-25th-anniversary-may resulted in:
This is interesting.
Since all the talk about LLMs and "AI" started, I've been hoping that someone would create a news app that is essentially self-hosted RSS server (like FreshRSS) + a personally trained LLM that would only serve me news it has learned I'm interested in. For example, I don't care about sports or celebrities and almost never want to see news about those topics. Conversely, I want news relevant to my geographical area, my area of work, and my hobby interests, etc.
Considering these can be run on consumer hardware, I think we're at the point where someone with the know-how just needs to connect the two.
I wonder if the news preferences could be loaded into a Modalfile so it can persist - as I understand it, this would be the only way preferences would survive separate chat sessions.
I love RSS but I have to be extremely choosy about which feeds I subscribe to because it can quickly become overwhelming given the number of articles posted daily.