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Show HN: Qwen-2.5-32B is now the best open source OCR model
41–50 of 51 posts
Re: Show HN: Qwen-2.5-32B is now the best open source OCR model
#42[deleted]
Re: Show HN: Qwen-2.5-32B is now the best open source OCR model
#43[deleted]
Re: Show HN: Qwen-2.5-32B is now the best open source OCR model
#44How does one configure an LLM interface using this to process multiple files with a single prompt?
Do you mean you want to process multiple files with a single LLM call or process multiple files using the same prompt across multiple LLM calls? (I would recommend the latter)
Multiple files with a single LLM call.
I have a prompt which works for a single file in Copilot, but it's slower than opening the file and looking at it to find one specific piece of information and re-saving it manually and then running a .bat file to rename with more of the information, then filling out the last two bits when entering things.
Re: Show HN: Qwen-2.5-32B is now the best open source OCR model
#45Re: Show HN: Qwen-2.5-32B is now the best open source OCR model
#46Downloading the MLX version of "Qwen2.5-VL-32b-Instruct -8bit" via LM Studio right now since it's not yet available on Ollama and I can run it locally... I have an OCR side project for it to work on, want to see how performant it is on my M4... will report back
I'm very curious about the results - I've been using mistral-ocr for the last 2 weeks and it worked really well.
Re: Show HN: Qwen-2.5-32B is now the best open source OCR model
#47Tesseract can manage 99% accuracy on anything other than handwriting. Without being an LLM.
Is there an advantage of using an LLM here?
Re: Show HN: Qwen-2.5-32B is now the best open source OCR model
#48How does one configure an LLM interface using this to process multiple files with a single prompt?
Depends what is your setup? You can always find more support on r/Localllama
Using Copilot, and currently running jan.ai --- /r/Localllama seems to tend towards the typical Reddit cesspool.
Let me rephrase:
What locally-hosted LLM would be suited to batch processing image files?
Re: Show HN: Qwen-2.5-32B is now the best open source OCR model
#49Earlier quoted context omitted.
One of these things is not like the others. $8.50/1000?? Any chance that's a typo? Otherwise, for someone that has no experience with LLM pricing models, why is Llama 90b so expensive?
It's not uncommon when using brokers to see outliers like this. What happens basically is that some models are very popular and have many different providers, and are priced "close to the metal" since the routing will normally pick the cheapest option with the specified requirements (like context size). But then other models - typically more specialized ones - are only hosted by a single provider, and said provider c…
I'll add that some, big-name suppliers with big models might be running at or near a loss on purpose to draw in customers. That behavior is often encouraged by funders who gave them over $100 million to capture the market.
Their theory is they can raise prices once their competitors go out of business. The companies open-sourcing pretrained models are countering that. So, we see a mix of huge models underpriced by scheming companies and open-source models priced for inference with free market principles.
Re: Show HN: Qwen-2.5-32B is now the best open source OCR model
#50Downloading the MLX version of "Qwen2.5-VL-32b-Instruct -8bit" via LM Studio right now since it's not yet available on Ollama and I can run it locally... I have an OCR side project for it to work on, want to see how performant it is on my M4... will report back
I'm very curious about the results - I've been using mistral-ocr for the last 2 weeks and it worked really well.
Its errors are interesting (averaging around one per paragraph). Semantically-correct, but wrong on precision (simple example, the English word "ardour" is transcripted as "ardor", and a foreign word like "palazzo" which is intended to remain so, is translated to "palace"). I'm still messing with temp/presence/frequency/top-p/top-k/prompting to see if I can squeeze some more precision out of it, but I'm running out of time.
Not sure if it matters but I exported a PDF page as a PNG with 200dpi resolution, and used that.
It seems like it's reading the text but getting the details wrong.
I would not be comfortable using this in an official capacity without more accuracy. I could see using this for words that another OCR system is uncertain about, though, as a fallback.