LocalLLaMA
Welcome to LocalLLaMA! Here we discuss running and developing machine learning models at home. Lets explore cutting edge open source neural network technology together.
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Rules:
Rule 1 - No harassment or personal character attacks of community members. I.E no namecalling, no generalizing entire groups of people that make up our community, no baseless personal insults.
Rule 2 - No comparing artificial intelligence/machine learning models to cryptocurrency. I.E no comparing the usefulness of models to that of NFTs, no comparing the resource usage required to train a model is anything close to maintaining a blockchain/ mining for crypto, no implying its just a fad/bubble that will leave people with nothing of value when it burst.
Rule 3 - No comparing artificial intelligence/machine learning to simple text prediction algorithms. I.E statements such as "llms are basically just simple text predictions like what your phone keyboard autocorrect uses, and they're still using the same algorithms since <over 10 years ago>.
Rule 4 - No implying that models are devoid of purpose or potential for enriching peoples lives.
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I think MiniCPM advertises with strong OCR capabilities. Maybe try that one. But is that 384 number correct? Seems to me even the common Llama 3.2 models do images up to 1120x1120px for a while and that should be enough. MiniCPM can do even more (1.8 million pixels).
Setup shouldn't be too hard. Lots of interfaces and inference frameworks have vision capabilities these days. It should work pretty much out of the box with something like Ollama, AnythingLLM or llama.cpp based stuff.
Other approaches include doing OCR by more traditional means and then feed the result into an LLM. Just make sure to check that whatever you use can read Chinese.
I'm not entirely sure what your prompt should look like. Obviously attach the image. With ChatGPT I believe I had a bit better results when I told it to first copy and write down the text, and then translate it in a second step. And then do whatever I want after that. I'm not sure what it does if you make it do everything in one go.
Thank you, haven’t heard of it before and it looks really interesting! I need to test how it works with llama.cpp, I wonder how it works with resolutions higher than supported, will it get downscaled
Most frontends should have you covered and scale down the image appropriately (and automatically). I'm not entirely sure about that. I think working on resolutions higher than supported should either not work due to the image encoder, or lead to degraded performance. Usually they're scaled to what the model needs, somewhere within the pipeline. You can crop them if you like, that sheds off some pixels. Or split them up and feed them in one part after the other, if that somehow makes sense. But I bet with most software you can just upload a random image and it'll do whatever scaling is required for you.
Managed to run it with llama.cpp. It was a great suggestion, thank you! MiniCPM-o-2_6 iq4 managed to read text from a picture of a shirt that gemma could not get right