Comment by nicce
1 day ago
> Gemma is open source and apache 2.0 licensed
Closed source but open weight. Let’s not ruin the definition of the term in advantage of big companies.
1 day ago
> Gemma is open source and apache 2.0 licensed
Closed source but open weight. Let’s not ruin the definition of the term in advantage of big companies.
Your reply adds more confusion, imo.
The inference code and model architecture IS open source[0] and there are many other high quality open source implementations of the model (in many cases contributed by Google engineers[1]). To your point: they do not publish the data used to train the model so you can't re-create it from scratch.
[0] https://github.com/google-deepmind/gemma [1] https://github.com/vllm-project/vllm/pull/2964
If for some reason you had the training data, is it even possible to create an exact (possibly same hash?) copy of the model? Seems like there are a lot of other pieces missing like the training harness, hardware it was trained on, etc?
to be entirely fair that's quite a high bar even for most "traditional" open source.
And even if you had the same data, there's no guarantee the random perturbations during training are driven by a PRNG and done in a way that is reproducible.
Reproducibility does not make something open source. Reproducibility doesn't even necessarily make something free software (under the GNU interpretation). I mean hell, most docker containers aren't even hash-reproducible.
Yes, this is true. A lot of times labs will hold back necessary infrastructure pieces that allow them to train huge models reliably and on a practical time scale. For example, many have custom alternatives to Nvidia’s NCCL library to do fast distributed matrix math.
Deepseek published a lot of their work in this area earlier this year and as a result the barrier isn’t as high as it used to be.
I am not sure if this adds even more confusion. Linked library is about fine-tuning which is completely different process.
Their publications about producing Gemma is not accurate enough that even with data you would get the same results.
In the README of the linked library they have a code snippet showing how to have a conversation with the model.
Also, even if it were for fine tuning, that would require an implementation of the model’s forward pass (which is all that’s necessary to run it).
1 reply →
Yes!! But I doubt how many are truly truly open source models since most just confuse open source with open weights and the definition has been changed really smh.