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Office space meme:
"If y'all could stop calling an LLM "open source" just because they published the weights... that would be great."
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this post was submitted on 28 Jan 2025
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Uuuuh… why?
Do you only accept open source code if you can see every key press every developer made?
Open source means you can recreate the binaries yourself. Neiter Facebook. Nor the devs of deepseek published which training data they used, nor their training algorithm.
They published the source code needed run the model. It’s open source in the way that anyone can download the model, run it locally, and further build on it.
Training from scratch costs millions.
Open source isn't really applicable to LLM models IMO.
There is open weights (the model), and available training data, and other nuances.
They actually went a step further and provided a very thorough breakdown of the training process, which does mean others could similarly train models from scratch with their own training data. HuggingFace seems to be doing just that as well. https://huggingface.co/blog/open-r1
It's worth noting that OpenR1 have themselves said that DeepSeek didn't release any code for training the models, nor any of the crucial hyperparameters used. So even if you did have suitable training data, you wouldn't be able to replicate it without re-discovering what they did.
OSI specifically makes a carve-out that allows models to be considered "open source" under their open source AI definition without providing the training data, so when it comes to AI, open source is really about providing the code that kicks off training, checkpoints if used, and details about training data curation so that a comparable dataset can be compiled for replicating the results.
Yeah, but not to train it
Yeah, it's about as open source as binary blobs.
So what? You still can gleam something if you know the dataset on which the model has been trained.
If software is hard to compile, can you keep the source code closed and still call software "open source"?
I agree the bad part is that they didn’t provide the script to train the model from scratch.
This is a great starting point for further improvements of the model. Most AI research is done with pretrained weights used as basis. Few are training models completely from scratch. The model is built with Torch, so anyone should be able to fine tune the model on custom data sets.
A software analogy:
Someone designs a compiler, makes it open source. Make an open runtime for it. 'Obtain' some source code with unclear license. Compiles it with the compiler and releases the compiled byte code that can run with the runtime on free OS. Do you call the program open source? Definitely it is more open than something that requires proprietary inside use only compiler and closed runtine and sometimes you can't access even the binary; it runs on their servers. It depends on perspective.
ps: the compiler takes ages and costs mils in hardware.
edit: typo
I think a more appropriate analogy is if you make an open source game. With the game you have made textures, because what is a game without textured surfaces? You include the binary jpeg images along with the source code.
You’ve made the textures with photoshop, which is a closed source application. The textures also features elements of stock photos. You don’t provide the original stock photos.
Anyone playing the game is free to replace the textures with their own. The game will have a different feel, but it’s still a playable game. Anyone is also free to modify the existing textures.
Would you consider this game closed source?
I'm going to take your point to the extreme.
It's only open source if the camera that took the picture that is used in the stock image that was used to create the texture is open source.
You used a fully mechanical camera and chemical flash powder? Better publish that design patent and include the chemistry of the flash powder!
And looking at mobile games like Tacticus, there are loads of people with millions to burn on hobbies
Eh, it seems like it fits to me. We casually refer to all manner of data as "open source" even if we lack the ability to specifically recreate it. It might be technically more accurate to say "open data" but we usually don't, so I can't be too mad at these folks for also not.
There's huge deaths of USGS data that's shared as open data that I absolutely cannot ever replicate.
If we're specifically saying that open source means you can recreate the binaries, then data is fundamentally not able to be open source, since it distinctly lacks any form of executable content.
lol, are you claiming data isn't reproducable? XD
Do you call binary-only software with EULA "Open Source" too?
Dude, the CPU instructions are right there, of course it's open source.
No, but I do call a CC licensed png file open source even if the author didn’t share the original layered Photoshop file.
Model weights are data, not code.
You'd be wrong. Open source has a commonly accepted definition and a CC licensed PNG does not fall under it. It's copyleft, yes, but not open source.
I do agree that model weights are data and can be given a license, including CC0. There might be some argument about how one can assign a license to weights derived from copyrighted works, but I won't get into that right now. I wouldn't call even the most liberally licensed model weights open-source though.
Fair enough, it’s not source code, so open source doesn’t apply.
It really comes down to this part of the "Open Source" definition:
A compiled binary is not the format in which a programmer would prefer to modify the program - it's much preferred to have the text file which you can edit in a text editor. Just because it's possible to reverse engineer the binary and make changes by patching bytes doesn't make it count. Any programmer would much rather have the source file instead.
Similarly, the released weights of an AI model are not easy to modify, and are not the "preferred format" that the internal programmers use to make changes to the AI mode. They typically are making changes to the code that does the training and making changes to the training dataset. So for the purpose of calling an AI "open source", the training code and data used to produce the weights are considered the "preferred format", and is what needs to be released for it to really be open source. Internal engineers also typically use training checkpoints, so that they can roll back the model and redo some of the later training steps without redoing all training from the beginning - this is also considered part of the preferred format if it's used.
OpenR1, which is attempting to recreate R1, notes: No training code was released by DeepSeek, so it is unknown which hyperparameters work best and how they differ across different model families and scales.
I would call "open weights" models actually just "self hostable" models instead of open source.
Thank you for the explanation. I didn’t know about the ‘preferred format’ definition or how AI models are changed at all.
Thank you for taking the time to write this. Making the rests reproducable and possible to improve on is important.
Open Source (generally and for AI) has an established definition.
https://opensource.org/ai/open-source-ai-definition
This is exactly it, open source is not just the availability of the machine instructions, it's also the ability to recreate the machine instructions. Anything less is incomplete.
It strikes me as a variation on the "free as in beer versus free as in speech" line that gets thrown around a lot. These weights allow you to use the model for free and you are free to modify the existing weights but being unable to re-create the original means it falls short of being truly open source. It is free as in beer, but that's it.
it's only open source if the source code is open.
source control management software like git lets you see basically this, yes.