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Comment by lmeyerov | Hacker News Reader

I've been mixed on this, it seems great for throwaway projects but a dead end for ones that survive:

* Out-of-the-box fine-tuned model for extraction makes for an easier start, so happy to see this out there

* ... But presumably one of the next steps in a project using it is doing further fine-tuning on their data after some use, but this is a closed model with closed data, so preserving the original fine tuning quality is unclear without that

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Hi there, CEO of NuMind here, absolutely agree, these models are meant to be fine-tuned to be really useful. Right now you can see how the input -> output are formatted in the model card on HuggingFace. From that you can create a set of input -> output and fine-tune NuExtract. We are working on a platform to make this fine-tuning easier.

Fair points. GLiNER is another model to consider: https://huggingface.co/urchade/gliner_medium-v2

Gliner is cc-by-nc-4. Seems like it's not licensed for commercial use?

Sorry, I referenced the older model. The v2 models are Apache 2.0.

Neat, afaict, if someone fine-tunes for their own data, the gliner stack is OSS so they may be able to just fork & rerun/continue

Where are you getting that it's a closed model? I'm seeing mit license on huggingface.

Where is the fine-tuning source code + data and with what license? Afaict that's the proprietary part which is why it isn't in their github and hf doesn't link to it.

Hence my comment that I don't see how to do further fine-tuning that doesn't just wipe out what this does. They did a free binary release of fine-tuned weights afaict, which is problematic for building a production data pipeline that you re-fine-tune over time.

I see. Yeah, I'd be interested in fine tuning as well on my own extractions. The tiny model even says it's meant to be fine tuned. I guess that's what they are commercializing :/

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