Thanks for your reply!

I have not used vs and cmake before, so I am probably making all newbie mistakes. I've sorted out that some paths where not set, and that C:\mingw-32\bin\make.exe doesn't exist but it's now minigw-make.exe.

Now I get the error that

   'C:/MinGW-32/bin/make.exe' '-?'

  failed with:

   C:/MinGW-32/bin/make.exe: invalid option -- ?

And from the few things I've found on-line I gathered it's because the mingw version doesn't support the option, but I should use Vs instead. I am a bit lost. Every time I manage to fix one issue, there's another one. :-)

As far as I know, the Meta license forbids this, since the model is for academic purposes only

and what does voting there do to make it open source? Lecun already knows that majority of people don't like this licensing as people were tweeting that at him since llama release...

It's most likely enforceable, but even if it's not they can simply ban OP for doing that. if OP is using their API in any way that's important to him, it's something to consider.

I think you'd be dismayed at how easy it is to enforce these things when you have OpenAI money.

Are you doing a Lora or full weights?

> I wanted to train Meta's LLaMA model on this data, but considering their license, I'm not sure if that is the best way. Suggestions will be appreciated.

If we ignore OpenAI's licence, is it ok to perhaps ignore Meta's licence as well? Or is that going too far

> The trained model will be open source, under MIT License.

Is the dataset going to be open source as well? So that other people can use it to train other models.

It's not about copyright

https://www.reddit.com/r/MachineLearning/comments/11v4h5z/-/jct0s11

They are. It's less to do with copyright and more to do with the fact that you signed the T&C before using their system ( and then broke ). It's simmilar to the LinkedIn data scraping case where the court ruled that it wasn't illegal for them to scrape ( nor did it violate copyright ) but they still got in trouble ( and had to settle ) because of violating the T&C.

One way around this is to have two parties, one generating and publishing the dataset ( doesn't violate T&C ) and another independant party ( who didn't sign the T&C ) fine-tuning a model on the dataset.

Just publish the diff. between the original model and the finetuned model. That's what a lot of people are doing to avoid any license issues.

• There's a already a couple high quality instruction datasets/compilations like FLAN that I think should also be mixed in.

• Be sure to check the generated dataset for issues. Might require some cleanup like the original did.

He's using the actual API.

I thought they didn't like ppl using the UI as an API? Hopefully you don't get banned

No they aren’t , they have no claim on transformers that would be google brain , but you don’t see alphabet throwing a sissy fit

Maybe set up the training code so different foundation models can be plugged in for finetuning and the it’s just compute if somebody wants a different starting model.

Note there are free interfaces to these models such as https://spellbook.scale.com/ . Also note there is a lot of data collected out there already.

Technically, I'm from Russia.

And, of course, you are able to read every opinion about "special military operation" here... sometimes even without VPN. It is just voicing a "different one" can get you for years into prison and your kids into a foster home for reindocrination. While the programmers that coded it might have a range diverse opinions on this and other "politically sensitive" subjects, if they would want their programm to pass inspection in China, they WILL have to do considerable fine-tuning to throw away sensitive data, if our Russian google (Yandex) frontpage is of any indictation. If this is a foundational model w/o finetunnig that's a different matter tho... but that it will hallucinate nonstop and produce "fakes" anyway...

Nice 👍 good project, I'm impatient to see the result. It would be great to make a torrent of the dataset to avoid unnecessary costs in the future too

Train a model that's designated as non-competing but open, then train another model from the output of that that's competing.

I've heard from some experienced testers that the 33B model is shockingly bad compared to even the 13B one. Despite what the benchmarks say. That we should either use the 65B one ( very good apparently ) or stick to 13B/7B. Not because of any technical reason but random luck/chance involved with training these models and the resultant quality.

I wonder if there's any truth to it. If you've tested it yourself, I'd love to hear what you thought.

It's what the copyright office said according to that midjourney comic that was being registered for copyright.

Since it was created by an AI the output cannot be registered for copyright and licensing doesn't hold power on something that's in public domain.

You can also query Codex for free. It might not be as good at ChatGPT, but perhaps still worth trying?

What? No it’s not. Pointing out blatant whataboutism is always independently valid.

Why would you even write what you wrote? Is it a required riposte that’s included in your briefing file, or training?

Will be interesting to see where lawmakers and courts ultimately land on this, but the current status quo is that AI generated text and images (or any other works) cannot be copyrighted. In other words for now all output is public domain and OpenAI can kick rocks on this. A TOS violation just means you might get banned from using their service lol.

Not sure how much this is established law.

Anyway, Alpaca says so themselves on their website: https://crfm.stanford.edu/2023/03/13/alpaca.html

>Careful. That MIT license won't work, I think, thanks to ClosedAIs licences

Generally, copyright requires human authorship. If the output of an AI model is solely generated by a machine without human input, it may not be eligible for copyright protection and fall under public domain.

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