[Trapais]

OK. Where is your reproduction of Pythia trained from scratch? Or MPT? Or Amber? Shall we play a game where you give paper regarding pretraining (and we are not taling about puny models based on wikitext2) I give you a paper based around finetuning and we'll see who run out of papers first?

[jncfhnb]

Reproduction is not the goal! Making papers is not the goal! Making useful models is the goal. And having open source models is by an enormous degree more useful thing.

I see you’re someone else, so I’ll ask you too. Do you actually have any experience doing this? Have you ever fine tuned models or tried to change architecture or put a piece of one model into another?

[Trapais]

>Making useful models is the goal.

Sure, training datasets for pythia is useful. The Pile was used in lots of models. However it's hardly relevant that pythia itself was trained on pile. They live separate lives.

Having just weights already allows making results that are incredibly useful(you don't need original dataset for flash attention, or tuning foundation model into the chat model).

Point is: Having both doesn't make released model more useful.

>Do you actually have any experience doing this? Have you ever fine tuned models or tried to change architecture or put a piece of one model into another?

Yes on both finetune and "changing" architecture: with adapters and similar approaches you don't need to retrain everything from scratch after modifying the guts of the original architecture up to your liking, you just need to not stir it up too much. Training on the task at hand is sufficient.

No, I haven't glued parts of existing models together(ensemble doesn't count)

[hn_acker]

> Reproduction is not the goal! Making papers is not the goal! Making useful models is the goal.

1. The thread is about the requirements of calling a model open source. The goal of making the models is separate from the requirements of the open source definition.

2. Suppose that author A of a model prefers working exclusively with the model weights to modify the model. Author A's preferred form of modification includes the model weights - and whatever scripts are needed to generate a running model from the weights - but does not include the training set and initial training scripts. Suppose that author B of an unrelated model prefers to retrain the model as part of the process of modifying the model. If author B changes the training set and/or changes the training scripts, then the training set is part of the preferred form of modifying the model. The training set and the training scripts are both necessary for turning the training set into a running model, so I think author B would have to include the training set even if author B changes only the training scripts. Correct me if I'm wrong.) jncfhnb, you're like author A, so if you were to release an open source model then you would need to include the weights but not the training data. Trapais and nullc, don't assume that every model author is author B.

For personal reference, here is the relevant excerpt from the open source definition from the Open Source Initiative [A1]:

> The source code must be the preferred form in which a programmer would modify the program. Deliberately obfuscated source code is not allowed. Intermediate forms such as the output of a preprocessor or translator are not allowed.

Open source software is not the same as free software, but here is the relevant excerpt from the free software definition explainer from the Free Software Foundation [A2]:

> Source code is defined as the preferred form of the program for making changes in. Thus, whatever form a developer changes to develop the program is the source code of that developer's version.

[A1] https://opensource.org/osd/

[A2] https://www.gnu.org/philosophy/free-sw.html

[anothernewdude]

> Reproduction is not the goal!

It is for Open Source. Hence why it's silly to call these models open source.