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.
@dandi8 but you are the one who is changing it. And who said it’s not feasible? Mixtral model is open-source. WizardLM2 is open-source. Phi3:mini is open-source… what’s your point?
But the license of the model is not related to the license of the data used for training, nor the license for the scripts and libraries. Those are three separate things.
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?
Looking at my open source model downloaded from the internet…
Yes?
What makes it open source?
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.
Just because open source AI is not feasible at the moment is no reason to change the definition of open source.
@dandi8 but you are the one who is changing it. And who said it’s not feasible? Mixtral model is open-source. WizardLM2 is open-source. Phi3:mini is open-source… what’s your point?
But the license of the model is not related to the license of the data used for training, nor the license for the scripts and libraries. Those are three separate things.
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?