Note that the OSI only ask for transparency of what the dataset was - a name and the fee paid will do - not that full access to it to be free and Free.
It’s worth mentioning too that they’ve used the MIT license for the “code” included with the model (a few YAML files to feed it to software) but they have created their own unrecognised non-free license for the model itself. Why they having this misleading label on their github page would only be speculation.
Without making the dataset available then nobody can accurately recreate, modify or learn from the model they’ve released. This is the only sane definition of open source available for an LLM model since it is not in itself code with a “source”.
Uh yeah, that’s because people publish data to huggingface. GitHub isn’t made for huge data files in case you weren’t aware. You can scroll down to datasets here https://huggingface.co/deepseek-ai
That’s the “prover” dataset, ie the evaluation dataset mentioned in the articles I linked you to. It’s for checking the output, it is not the training output.
It’s also 20mb, which is miniscule not just for a training dataset but even as what you seem to think is a “huge data file” in general.
You really need to stop digging and admit this is one more thing you have surface-level understanding of.
Since you’re definitely asking this in good faith and not just downvoting and making nonsense sealion requests in an attempt to make me shut up, sure! Here’s three.
Oh, and it’s not me demanding. It’s the OSI defining what an open source AI model is. I’m sure once you’ve asked all your questions you’ll circle back around to whether you disagree with their definition or not.
Thank you for posting those links, while I’m not sure the person you replied to was asking in good faith, I myself was wanting to see an example after reading the discussion.
Seems like even if it’s not fully open source it’s a step in the right direction in a world where terms like “open” and non profit have been co-opted by corporations to lose their original meaning.
It’s certainly better than "Open"AI being completely closed and secretive with their models. But as people have discovered in the last 24 hours, DeepSeek is pretty strongly trained to be protective of the Chinese government policy on, uh, truth. If this was a truly Open Source model, someone could “fork” it and remake it without those limitations. That’s the spirit of “Open Source” even if the actual term “source” is a bit misapplied here.
As it is, without the original training data, an attempt to remake the model would have the issues DeepSeek themselves had with their “zero” release where it would frequently respond in a gibberish mix of English, Mandarin and programming code. They had to supply specific data to make it not do this, which we don’t have access to.
So you found a legacy data set that’s been released nearly a year ago as your best example. Thanks for proving my point. And since you obviously know what you’re talking about, do explain to the class what stops people from using these data sets to train a DeepSeek model?
What I do know is that you can take DeepSeek model and train it on this open crawl to get a fully open model. I love how you ignored this part in your reply being the clown that you are.
I ignored the bit you edited in after I replied? And you’re complaining about ignoring questions in general? Do you disagree with the OSI definition Yogsy? You feel ready for that question yet?
What on earth do you even mean “take a model and train it on thos open crawl to get a fully open model”? This sentence doesn’t even make sense. Never mind that that’s not how training a model works - let’s pretend it is. You understand that adding open source data to closed source data wouldn’t make the closed source data less closed source, right?.. Right?
Thank fuck you’re not paid real money for this Yiggly because they’d be looking for their dollars back
The data part. ie the very first part of the OSI’s definition.
It’s not available from their articles https://arxiv.org/html/2501.12948v1 https://arxiv.org/html/2401.02954v1
Nor on their github https://github.com/deepseek-ai/DeepSeek-LLM
Note that the OSI only ask for transparency of what the dataset was - a name and the fee paid will do - not that full access to it to be free and Free.
It’s worth mentioning too that they’ve used the MIT license for the “code” included with the model (a few YAML files to feed it to software) but they have created their own unrecognised non-free license for the model itself. Why they having this misleading label on their github page would only be speculation.
Without making the dataset available then nobody can accurately recreate, modify or learn from the model they’ve released. This is the only sane definition of open source available for an LLM model since it is not in itself code with a “source”.
Uh yeah, that’s because people publish data to huggingface. GitHub isn’t made for huge data files in case you weren’t aware. You can scroll down to datasets here https://huggingface.co/deepseek-ai
That’s the “prover” dataset, ie the evaluation dataset mentioned in the articles I linked you to. It’s for checking the output, it is not the training output.
It’s also 20mb, which is miniscule not just for a training dataset but even as what you seem to think is a “huge data file” in general.
You really need to stop digging and admit this is one more thing you have surface-level understanding of.
Do show me a published data set of the kind you’re demanding.
Since you’re definitely asking this in good faith and not just downvoting and making nonsense sealion requests in an attempt to make me shut up, sure! Here’s three.
https://commoncrawl.org/
https://github.com/togethercomputer/RedPajama-Data
https://huggingface.co/datasets/legacy-datasets/wikipedia/tree/main/
Oh, and it’s not me demanding. It’s the OSI defining what an open source AI model is. I’m sure once you’ve asked all your questions you’ll circle back around to whether you disagree with their definition or not.
Thank you for posting those links, while I’m not sure the person you replied to was asking in good faith, I myself was wanting to see an example after reading the discussion.
Seems like even if it’s not fully open source it’s a step in the right direction in a world where terms like “open” and non profit have been co-opted by corporations to lose their original meaning.
It’s certainly better than "Open"AI being completely closed and secretive with their models. But as people have discovered in the last 24 hours, DeepSeek is pretty strongly trained to be protective of the Chinese government policy on, uh, truth. If this was a truly Open Source model, someone could “fork” it and remake it without those limitations. That’s the spirit of “Open Source” even if the actual term “source” is a bit misapplied here.
As it is, without the original training data, an attempt to remake the model would have the issues DeepSeek themselves had with their “zero” release where it would frequently respond in a gibberish mix of English, Mandarin and programming code. They had to supply specific data to make it not do this, which we don’t have access to.
So you found a legacy data set that’s been released nearly a year ago as your best example. Thanks for proving my point. And since you obviously know what you’re talking about, do explain to the class what stops people from using these data sets to train a DeepSeek model?
The most recent crawl is from December 15th
https://commoncrawl.org/blog/december-2024-crawl-archive-now-available
You don’t know, and can’t know, when DeepSeeker’s dataset is from. Thanks for proving my point.
What I do know is that you can take DeepSeek model and train it on this open crawl to get a fully open model. I love how you ignored this part in your reply being the clown that you are.
I ignored the bit you edited in after I replied? And you’re complaining about ignoring questions in general? Do you disagree with the OSI definition Yogsy? You feel ready for that question yet?
What on earth do you even mean “take a model and train it on thos open crawl to get a fully open model”? This sentence doesn’t even make sense. Never mind that that’s not how training a model works - let’s pretend it is. You understand that adding open source data to closed source data wouldn’t make the closed source data less closed source, right?.. Right?
Thank fuck you’re not paid real money for this Yiggly because they’d be looking for their dollars back