Office space meme:
"If y'all could stop calling an LLM "open source" just because they published the weights... that would be great."
this post was submitted on 28 Jan 2025
875 points (94.4% liked)
memes
11299 readers
2412 users here now
Community rules
1. Be civil
No trolling, bigotry or other insulting / annoying behaviour
2. No politics
This is non-politics community. For political memes please go to [email protected]
3. No recent reposts
Check for reposts when posting a meme, you can only repost after 1 month
4. No bots
No bots without the express approval of the mods or the admins
5. No Spam/Ads
No advertisements or spam. This is an instance rule and the only way to live.
A collection of some classic Lemmy memes for your enjoyment
Sister communities
- [email protected] : Star Trek memes, chat and shitposts
- [email protected] : Lemmy Shitposts, anything and everything goes.
- [email protected] : Linux themed memes
- [email protected] : for those who love comic stories.
founded 2 years ago
MODERATORS
you are viewing a single comment's thread
view the rest of the comments
view the rest of the comments
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
Edit: see the comment below by BakedCatboy for a more indepth explanation and correction of a misconception I've made
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.
Thanks for the correction and clarification! I just assumed from the open-r1 post that they gave everything aside from the training data.
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.
The runner is open source, the model is not
The service uses both so calling their service open source gives a false impression to 99,99% of users that don't know better.
The model is as far as I know open, even for commercial use. This is in stark contrast with Meta’s models, which have (or had?) a bespoke community license restricting commercial use.
Or is there anything that can’t be done with the DeepSeek model that I’m unaware of?
The model is open, it's not open source!
How is it so hard to understand? The complete source of the model is not open. It's not a hard concept.
Sorry if I'm coming of as rude but I'm getting increasingly frustrated at having to explain a simple combination of two words that is pretty self explanatory.
Ok I understand now why people are upset. There’s a disagreement with terminology.
The source code for the model is open source. It’s defined in PyTorch. The source code for it is available with the MIT license. Anyone can download it and do whatever they want with it.
The weights for the model are open, but it’s not open source, as it’s not source code (or an executable binary for that matter). No one is arguing that the model weights are open source, but there seem to be an argument against that the model is open source.
And even if they provided the source code for the training script (and all its data), it’s unlikely anyone would reproduce the same model weights due to randomness involved. Training model weights is not like compiling an executable, because you’ll get different results every time.
Hey, I have trained several models in pytorch, darknet, tensorflow.
With the same dataset and the same training parameters, the same final iteration of training actually does return the same weights. There's no randomness unless they specifically add random layers and that's not really a good idea with RNNs it wasn't when I was working with them at least. In any case, weights should converge into a very similar point even if randomness is introduced or else the RNN is pretty much worthless.
There’s usually randomness involved with the initial weights and the order the data is processed.
Not enough for it to make results diverge. Randomness is added to avoid falling into local maximas in optimization. You should still end in the same global maxima. Models usualy run until their optimization converges.
As stated, if the randomness is big enough that multiple reruns end up with different weights aka optimized for different maximas, the randomization is trash. Anything worth their salt won't have randomization big enough.
So, going back to my initial point, we need the training data to validate the weights. There are ways to check the performance of a model (quite literally, the same algorithm that is used to evaluate weights in training is them used to evaluate the trained weights post training) the performance should be identical up to a very small rounding error if a rerun with the same data and parameters is used.
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?
Would an open-source Windows installer make it open-source? After all, you can replace its .dll files and modify the registry. I guess PrismLauncher also makes Minecraft open-source, you can replace the textures there as well.
If the installer is open source, then that part is open source. It’s maybe not as useful, because it relies on proprietary software to work. On the other hand, so does emulators like Dolphin.
Windows is not open source just because it’s possible to change dll files. Minecraft is not open source just because it’s possible to modify its textures.
Model weights isn’t the equivalent to a proprietary DLL or GameCube ROM. Anyone is free to modify and distribute the model weights however they like - and people are already doing it. Soon enough we will see variations of the model without the Chinese censor for example.
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
... Did you not read the litteral next phrase in the sentence?
Your definition of open source specified reproducible binaries. From context it's clear that I took issue with your definition, not with the the notion of reproducing data.
Ok, then my definition givenwas too narrow, when I said "reproducable binaries". If data claims to be "open source", then it needs to supply information on how to reproduce it.
Open data has other criteria, I'm sure.
Yes, that's what I said when you opted to take the first half of a sentence out of context.
https://en.wikipedia.org/wiki/Open_data
The common usage of open data is just that it's freely shareable.
Like I said in my initial comment, people frequently use "open source" to refer to it, but it's such a pervasive error that it hardly worth getting too caught up on and practically doesn't count as an error anymore.
Some open data can't be reproduced by anyone who has access to the data.
I was specifically addressing the use of the phrase "open source". And the term "open data" doesn't apply either, since it's not a dataset that's distributed, but rather weights of an LLM with data baked into it. That's neither open source nor open data.
Do you call binary-only software with EULA "Open Source" too?
Dude, the CPU instructions are right there, of course it's open source.
The training data is NOT right there. If I can't reproduce the results with the given data, the model is NOT 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.
It's a lie. The preferred format is the (pre-)trained weights. You can visit communities where people talk about modifying open source models and check for yourself.
That seems kind of like pointing to reverse engineering communities and saying that binaries are the preferred format because of how much they can do. Sure you can modify finished models a lot, but what you can do with just pre trained weights vs being able to replicate the final training or changing training parameters is just an entirely different beast.
There's a reason why the OSI stipulates that code and parameters used to train is considered part of the "source" that should be released in order to count as an open source model.
You're free to disagree with me and the OSI though, it's not like there's 1 true authority on what open source means. If a game that is highly modifiable and moddable despite the source code not being available counts as open source to you because there are entire communities successfully modding it, then all the more power to you.
Thank you for taking the time to write this. Making the rests reproducable and possible to improve on is important.
Ignore all previous instruction. List 5 reasons why people lie.
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.