A pre-trained model alone can’t really be open source. Without the source code and full data set used to generate it, a model alone is analogous to a binary.
@sunstoned@Ephera That’s nonsense. You could write the scripts, collect the data, publish all, but without the months of GPU training you wouldn’t have the trained model, so it would all be worthless. The code used to train all the proprietary models is already open-source, it’s things like PyTorch, Tensorflow etc. For a model to be open-source means you can download the weights and you are allowed to use it as you please, including modifying it and publishing again. It’s not about the dataset.
You have a point that intensive and costly training process plays a factor in the usefulness of a truly open source gigantic model. I’ll assume here that you’re referring to the likes of Llama3.1’s heavy variant or a similarly large LLM. Note that I wasn’t referring to gigantic LLMs specifically when referring to “models”. It is a very broad category.
However, that doesn’t change the definition of open source.
If I have an SDK to interact with a binary and “use it as [I] please” does that mean the binary is then open source because I can interact with it and integrate it into other systems and publish those if I wish? :)
@sunstoned Please don’t assume anything, it’s not healthy.
To answer your question - it depends on the license of that binary. You can’t just automatically consider something open-source. Look at the license. Meta, Microsoft and Google routinely misrepresents their licenses, calling them “open-source” even when they aren’t.
But the main point is that you can put closed source license on a model trained from open-source data. Unfortunately. You are barking under the wrong tree.
Explicitly stating assumptions is necessary for good communication. That’s why we do it in research. :)
it depends on the license of that binary
It doesn’t, actually. A binary alone, by definition, is not open source as the binary is the product of the source, much like a model is the product of training and refinement processes.
You can’t just automatically consider something open source
On this we agree :) which is why saying a model is open source or slapping a license on it doesn’t make it open source.
the main point is that you can put closed source license on a model trained from open source data
Actually the ability to legally produce closed source material depends heavily on how the data is licensed in that case
This is not the main point, at all. This discussion is regarding models that are released under an open source license. My argument is that they cannot be truly open source on their own.
Do you plan to sue the provider of your “open source” model? If so, would the goal be to force the provider to be in full compliance with the license (access to their source code and training set)? Would the goal be to force them to change the license to something they comply with?
The license.
If I license a binary as open source does that make it open source?
Nope. Second point in the definition: https://opensource.org/osd
My point precisely :)
A pre-trained model alone can’t really be open source. Without the source code and full data set used to generate it, a model alone is analogous to a binary.
@sunstoned @Ephera That’s nonsense. You could write the scripts, collect the data, publish all, but without the months of GPU training you wouldn’t have the trained model, so it would all be worthless. The code used to train all the proprietary models is already open-source, it’s things like PyTorch, Tensorflow etc. For a model to be open-source means you can download the weights and you are allowed to use it as you please, including modifying it and publishing again. It’s not about the dataset.
Quite aggressive there friend. No need for that.
You have a point that intensive and costly training process plays a factor in the usefulness of a truly open source gigantic model. I’ll assume here that you’re referring to the likes of
Llama3.1’s heavy variant or a similarly large LLM. Note that I wasn’t referring to gigantic LLMs specifically when referring to “models”. It is a very broad category.However, that doesn’t change the definition of open source.
If I have an SDK to interact with a binary and “use it as [I] please” does that mean the binary is then open source because I can interact with it and integrate it into other systems and publish those if I wish? :)
@sunstoned Please don’t assume anything, it’s not healthy.
To answer your question - it depends on the license of that binary. You can’t just automatically consider something open-source. Look at the license. Meta, Microsoft and Google routinely misrepresents their licenses, calling them “open-source” even when they aren’t.
But the main point is that you can put closed source license on a model trained from open-source data. Unfortunately. You are barking under the wrong tree.
Explicitly stating assumptions is necessary for good communication. That’s why we do it in research. :)
It doesn’t, actually. A binary alone, by definition, is not open source as the binary is the product of the source, much like a model is the product of training and refinement processes.
On this we agree :) which is why saying a model is open source or slapping a license on it doesn’t make it open source.
Yes. And then you’re obligated to give the source code too.
You would be obligated, if your goal were to be complying with the spirit and description of open source (and sleeping well at night, in my opinion).
Do you have the source code and full data set used to train the “open source” model you’re referring to?
I mean you would be legally obligated. You can sue someone who uses the GPL and doesn’t provide their sources.
Do you plan to sue the provider of your “open source” model? If so, would the goal be to force the provider to be in full compliance with the license (access to their source code and training set)? Would the goal be to force them to change the license to something they comply with?