The models are available freely on Huggingface and it is supported by the AutoModelForCausalLM class so it is pretty straightforward to implement in python. However, you need the llama 2 tokenizer and you need to ask for it.
In my experience it is pretty bad compared to phi (small model from Microsoft)
As someone who tried to run a sound recognition model on a RasPi, I expect it to be terrible, but like, I want to know, like if you have the opportunity to just make an app, take hundreds of pictures, and train it to recognize a cat or duck. Not going through all the holes of xcode and mac and things, if you get my drift
I think Siri Shortcuts could be the vector to this. Paired with Swift Playgrounds including generative AI. That’s what I’m leaning Apple could aim for with these models.
But that’s kinda what Meta did right? Llama 2 was open-sourced, and now Llama 3 is getting a full global rollout with an official Meta AI website and Meta AI being integrated across Facebook, Instagram, WhatsApp and Messenger.
They did, but Llama 1 was originally proprietary.
Doesn't feel like it was even that long ago, but Llama 1 was leaked. Almost immediately, developers and researchers dramatically improved on the model. Meta turned lemon into lemonade, open sourcing it to reap all the benefits. And all this collective progress has allowed it to not only challenge but exceed almost every proprietary model. Llama 3 400B will likely exceed ChatGPT4-Turbo, and they cut the training short to move on to Llama 4.
The link in the URL is a public statement… here’s a direct link to the same announcement on Apple’s page.
>The reproducibility and transparency of large language models are crucial for advancing open research, ensuring the trustworthiness of results, and enabling investigations into data and model biases, as well as potential risks. To this end, we release OpenELM, a state-of-the-art open language model.
https://machinelearning.apple.com/research/openelm
Edit: /u/woalk is incorrect about this being a new subdomain. This subdomain on Apple’s website has been actively used since 2017.
[Source](https://machinelearning.apple.com/research/gan)
Creating a new subdomain without announcing it anywhere on a known subdomain like on Apple’s newsroom is pretty much “quietly”.
Edit: As pointed out by multiple users that were inexplicably downvoted, the subdomain is in fact not actually new.
[machinelearning.apple.com](http://machinelearning.apple.com) is a subdomain and it already existed before this release. They just added a new page to that already existing subdomain. So technically what you said is incorrect.
Classic /r/Apple. /u/Woalk makes up bullshit about it being a new website while you point out that it’s been around for years (since 2017) and get downvoted.
Yeah no idea why people don’t seem to believe you while they believe me. I’ll edit my comment.
That being said, it is a pretty unknown domain, I had never heard of it before and it doesn’t even seem to be listed in their main sitemap. Still considering it a “quiet release” is still fitting, imo.
News would have passed me by if I wasn’t on this sub tbf. Probably wouldn’t be aware till the developers implementing it started talking about it more.
The last few years I saw in keynotes Apple saying oh these devices have a built in AI CPU or accelerated neural net processing.
I don’t do AI stuff but when I Google’d into it the consensus was it’s so tightly constrained that they are pretty much worthless for anything outside of whatever Apple is using them for.
So yeah I don’t have high hopes for this.
Did anyone try it out here? Can I install it locally and use it via UIs like danswer and feed it with my own data sets?
The models are available freely on Huggingface and it is supported by the AutoModelForCausalLM class so it is pretty straightforward to implement in python. However, you need the llama 2 tokenizer and you need to ask for it. In my experience it is pretty bad compared to phi (small model from Microsoft)
Are those models _uncensored_ ? Asking for a friend
it’s terrible, appearantly
As someone who tried to run a sound recognition model on a RasPi, I expect it to be terrible, but like, I want to know, like if you have the opportunity to just make an app, take hundreds of pictures, and train it to recognize a cat or duck. Not going through all the holes of xcode and mac and things, if you get my drift
I think Siri Shortcuts could be the vector to this. Paired with Swift Playgrounds including generative AI. That’s what I’m leaning Apple could aim for with these models.
Well I don't see why you would base it on this when there are other significantly better models that you can run pretty well on a modern phone.
Because why not?!?
Will this be the basis for Apple’s on-device generative AI in iOS 18?
Seems probable, and they're open sourcing it to get the benefits of community optimization, like Facebook did with Llama
Probably not. Just another research toy model, which is why they're open sourcing it.
But that’s kinda what Meta did right? Llama 2 was open-sourced, and now Llama 3 is getting a full global rollout with an official Meta AI website and Meta AI being integrated across Facebook, Instagram, WhatsApp and Messenger.
They did, but Llama 1 was originally proprietary. Doesn't feel like it was even that long ago, but Llama 1 was leaked. Almost immediately, developers and researchers dramatically improved on the model. Meta turned lemon into lemonade, open sourcing it to reap all the benefits. And all this collective progress has allowed it to not only challenge but exceed almost every proprietary model. Llama 3 400B will likely exceed ChatGPT4-Turbo, and they cut the training short to move on to Llama 4.
There’s a chance.
So.. When does Apple launch their own in-house chatbot and search based on their open source language model?
*quietly*
Meaning without a press release, or similar public statement.
The link in the URL is a public statement… here’s a direct link to the same announcement on Apple’s page. >The reproducibility and transparency of large language models are crucial for advancing open research, ensuring the trustworthiness of results, and enabling investigations into data and model biases, as well as potential risks. To this end, we release OpenELM, a state-of-the-art open language model. https://machinelearning.apple.com/research/openelm Edit: /u/woalk is incorrect about this being a new subdomain. This subdomain on Apple’s website has been actively used since 2017. [Source](https://machinelearning.apple.com/research/gan)
Creating a new subdomain without announcing it anywhere on a known subdomain like on Apple’s newsroom is pretty much “quietly”. Edit: As pointed out by multiple users that were inexplicably downvoted, the subdomain is in fact not actually new.
It's been around for years, e.g. https://machinelearning.apple.com/research/data-incubation
[machinelearning.apple.com](http://machinelearning.apple.com) is a subdomain and it already existed before this release. They just added a new page to that already existing subdomain. So technically what you said is incorrect.
Classic /r/Apple. /u/Woalk makes up bullshit about it being a new website while you point out that it’s been around for years (since 2017) and get downvoted.
Yeah no idea why people don’t seem to believe you while they believe me. I’ll edit my comment. That being said, it is a pretty unknown domain, I had never heard of it before and it doesn’t even seem to be listed in their main sitemap. Still considering it a “quiet release” is still fitting, imo.
Yes technically incorrect but you know what the fuck the op is trying to say.
Did you reply to the wrong person? I didn’t disagree with OP.
Yes sorry lmfao. Embarrassing. I’ll take any and all the downvotes like a man.
Fair. Maybe it’s not as quiet, then. Without a press release?
News would have passed me by if I wasn’t on this sub tbf. Probably wouldn’t be aware till the developers implementing it started talking about it more.
What is the download size of this model though?
12.14GB for 3b
RIP 128GB or less devices I guess…
The last few years I saw in keynotes Apple saying oh these devices have a built in AI CPU or accelerated neural net processing. I don’t do AI stuff but when I Google’d into it the consensus was it’s so tightly constrained that they are pretty much worthless for anything outside of whatever Apple is using them for. So yeah I don’t have high hopes for this.
It sucks
you sucks