I spun up ollama and paperless-gpt to add ai ocr sidecar to paperless-ngx. It's okay. It can read handwritten stuff okayish, which is better than tesseract (doesnt read hand writing at all), so I throw handwritten stuff to it, but the difference on typed text is marginal in my single day I spent testing 3 different models on a few different typed receipts.
this post was submitted on 12 Mar 2025
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I run kobold.cpp which is a cutting edge local model engine, on my local gaming rig turned server. I like to play around with the latest models to see how they improve/change over time. The current chain of thought thinking models like deepseek r1 distills and qwen qwq are fun to poke at with advanced open ended STEM questions.
STEM questions like "What does Gödel's incompleteness theorem imply about scientific theories of everything?" Or "Could the speed of light be more accurately refered to as 'the speed of causality'?"
As for actual daily use, I prefer using mistral small 24b and treating it like a local search engine with the legitimacy of wikipedia. Its a starting point to ask questions about general things I don't know about or want advice on, then do further research through more legitimate sources.
Its important to not take the LLM too seriously as theres always a small statistical chance it hallucinates some bullshit but most of the time its fairly accurate and is a pretty good jumping off point for further research.
Lets say I want an overview of how can I repair small holes forming in concrete, or general ideas on how to invest financially, how to change fluids in a car, how much fat and protein is in an egg, ect.
If the LLM says a word or related concept I don't recognize I grill it for clarifying info and follow it through the infinite branching garden of related information.
I've used an LLM to help me go through old declassified documents and speculate on internal gov terminalogy I was unfamiliar with.
I've used a speech to text model and get it to speek just for fun. Ive used multimodal model and get it to see/scan documents for info.
Ive used websearch to get the model to retrieve information it didn't know off a ddg search, again mostly for fun.
Feel free to ask me anything, I'm glad to help get newbies started.
I use OLlama & Open-WebUI, OLlama on my gaming rig and Open-WebUI as a frontend on my server.
It's been a really powerful combo!
Would you please talk more about it. I forgot about Open-webui, but intending to start playing with. Honestly, what do you actually do with it?
I have this exact same setup. Open Web UI has more features than I've been able to use such as functions and pipelines.
I use it to share my LLMs across my network. It has really good user management so I can set up a user for my wife or brother in law and give them general use LLM while my dad and I can take advantage of Coding-tuned models.
The code formatting and code execution functions are great. It's overall a great UI.
Ive used LLMs to rewrite code, help format PowerPoint slides, summarize my notes from work, create D&D characters, plan lessons, etc
I have Linkwarden pointed at my ollama deployment, so it auto tags links that I archive which is nice.
I've seen other people send images captured on their security cameras on frigate to ollama to get it to describe the image
There's a bunch of other use cases I've thought of for coding projects, but haven't started on any of them yet
I have the same setup, but its not very usable as my graphics card has 6gb ram. I want one with 20 or 24, as the 6b models are pain and the tiny ones don’t give me much.
Ollama was pretty easy to set up on windows, and its eqsy to download and test the models ollama has available
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Sex chats. For other uses, just simple searches are better 99% of the time. And for the 1%, something like the Kagis FastGPT helps to find the correct keywords.
None currently. Wish I could afford a GPU to play with some stuff.
Yeah. I have a mini PC with an AMD GPU. Even if I were to buy a big GPU I couldn't use it. That frustrates me, because I'd love to play around with some models locally. I refuse to use anything hosted by other people.
Most LLM projects support Vulkan if you have enough VRAM
Your M.2 port can probably fit an M.2 to PCIe adapter and you can use a GPU with that - ollama supports AMD GPUs just fine nowadays (well, as well as it can, rocm is still very hit or miss)
Oh, then I need to give it another try.
Check rocm's supported cards, oh and after you install rocm, restart your computer - made that mistake when I was doing it and couldn't figure out why it wasn't working.
Well, let me know your suggestions if you wish. I took the plunge and am willing to test on your behalf, assuming I can.
I messed around with home assistant and the ollama integration. I have passed on it and just use the default one with voice commands I set up. I couldn't really get ollama to do or say anything useful. Like I asked it what's a good time to run on a treadmill for beginners and it told me it's not a doctor.
Like I asked it what's a good time to run on a treadmill for beginners and it told me it's not a doctor.
Kirkland brand meseeks energy.
Hey now Kirkland brand is respectable, usually premium brands repackaged. Such as how Costco vodka was secretly ("secretly") Grey Goose
There are some experimental models made specifically for use with Home Assistant, for example home-llm.
Even though they are tiny 1-3B I've found them to work much better than even 14B general purpose models. Obviously they suck for general purpose questions just by their size alone.
That being said they're still LLMs. I like to keep the "prefer handling commands locally" option turned on and only use the LLM as a fallback.
Sounds like ollama was loaded up with an either overly censored or plain brain dead language model. Do you know which model it was? Maybe try mistral if it fits in your computer.
Haha, that is hilarious. Sounds like it gave you some snark. afaik you have to clarify by asking again when it says such things. "I'm not asking for medical advice, but..."
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I have Immich that has AI searching for my photos. Pretty useful for finding stuff actually
Once I changed the default model, immich search became amazing. I want to show it off to people but alas, way too many NSFW pics in my library. I would create a second "clean" version to show off to people but I've been too lazy.
Can't you tag the NSFW to filter it out?
LMStudio is pretty much the standard. I think it's opensource except for the UI. Even if you don't end up using it long-term, it's great for getting used to a lot of the models.
Otherwise there's OpenWebUI that I would imagine would work as a docker compose, as I think there's ARM images for OWU and ollama
Well they are fully closed source except for the open source project they are a wrapper on. The open source part is llama.cpp
Fair enough, but it's damn handy and simple to use. And I don't know how to do speculative decoding with ollama, which massively speeds up the models for me.
Their software is pretty nice. That's what I'd recommand to someone who doesn't want to tinker. It's just a shame they don't want to open source their software and we have to reinvent the wheel 10 times. If you are willing to tinker a bit koboldcpp + openewebui/librechat is a pretty nice combo.
That koboldcpp is pretty interesting. Looks like I can load a draft model for spec decode as well as a pile of other things.
What local models have you been using for coding? I've been disappointed with things like deepseek-coder and the qwen-coder, it's not even a patch on Claude, but that damn cost for anthropic has been killing me.
As much as I'd like to praise the open-weight models. Nothing comes close to Claude sonnet in my experience too. I use local models when info are sensitive and claude when the problem requires being somewhat competent.
What setup do you use for coding? I might have a tip for minimizing claude cost you depending on what your setup is.
I'm using vscode/Roocode with Gosucoder shortprompt, with Requesty providing models. Generally I'll use R1 to outline a project and Claude to implement. The shortprompt seems to reduce the context quite a bit and hence the cost. I've heard about Cursor but haven't tried it yet.
When you're using local models, which ones are you using? The ones I mention don't seem to give me much I can use, but I'm also probably asking more of them because I see what Claude can do. It might also be a problem with how Roocode uses them, though when I just jump into a chat and ask it to spit out code, I don't get much better.
If you are willing to pay 10$ a month. You should get GithubCopilot, it provides near unlimited claude 3.5 usage. RooCode can hook into the github copilot api, and use it for its generations.
I use Qwen Coder and Mistral small locally too. It works ok, but its nowhere near GPT/Claude in terms of response quality.
I run ollama and auto1111 on my desktop when it's powers on. Using open-webui in my homelab always on, and also connected to openrouter. This way I can always use openwebui with openrouter models and it's pretty cheap per query and a little more private that using a big tech chatbot. And if I want local, I turn on the desktop and have local lamma and stab diff.
I also get bugger all benefit out of it., it's a cute toy.
I’ve an old gaming PC with a decent GPU laying around and I’ve thought of doing that (currently use it for linux gaming and GPU related tasks like photo editing etc) However ,I’m currently stuck using LLMs on demand locally with ollama. Energy costs of having it powered on all time for on demand queries seems a bit overkill to me…
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I have immich machine learning and ollama with openwebui
I use immich search a lot to find things like pictures of the side of the road to post on my community [email protected]
I almost never use the ollama though, not really sure what to do with it other than ask it dumb questions just to see what it says
I use the duckduckgo one when it auto has an answer to something I searched but its not too reliable
Try running an AI Horde worker, it's a really great service!
Not sure I know what that is. As in Hoarder?
It's a cluster of workers where everyone can generate images/text using workers connected to the service.
So if you ran a worker, people could generate stuff using your PC. For that you would gain kudos, which in turn you can use to generate stuff on other people's computers.
Basically you do two things: help common people without access to powerful machines and use your capacity when you have time to use the kudos whenever you want, even on the road where you can't turn on your PC if you fancy so.
I was able to run a distilled version of DeepSeek on Linux. I ran it inside a PODMAN container with ROCM support (I have an AMD GPU). It wasn't super fast but for a locally deployed and self hosted option the performance was okay. Apart from that I have deployed Fooocus for image generation in a similar manner. Currently, I am working on deploying Stable Diffusion with either ComfyUI or Automatic1111 inside a PODMAN container with ROCM support.
Didn't know about these image generation tools, besides Stable Diffusion. Thanks!
Can anyone suggest a model for light coding? I'm on a 3070 mobile.
Qwen coder or the new gemma3.
But at this size using privacy respecting api might be both cheaper and lead to better results.
Claude is the standard that all others are judged by. But it's not cheap.
Gemini is pretty good, and Qwen-coder isn't bad. I'd suggest you watch a few vids on GosuCoder's YT channel to see what works for you, he reviews a pile of them and it's quite up to date.
And if you use VScode, I highly recommend the Roocode extension. Gosucoder also goes into revising the roocode prompt to reduce costs for Claude. Another extension is Cline.
I am curious about trying an application specific AI. Like just for coding, for instance. I assume the memory requirements would be much lower.
afaik Ollama would fit that bill, but perhaps others can chime in. You could probably run it on your local computer with a small model based on CPU alone.
I haven’t sunk much time at it, but I’m not aware of any training data focusing on code only. There’s nothing preventing me from running with general purpose data, but I imagine I’d have a snappier response with a smaller, focused dataset, without losing accuracy.
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