Why'd it drop today? One supposes that instead of pressing shift+delete on their repo they click publish now so they get to write the headline that 2 big tech companies release small language models on the same day.
I retract the claim of proprietary. I misunderstood some of the licence wording. The license appears to be well accepted as a permissive open source license. https://spdx.org/licenses/AML.html
OpenELM, a family of Efficient Language Models Developed by Apple, is trending on Hugging Face!
OpenELM offers models with 270M to 3B parameters, pre-trained and instruction-tuned, with Good results across various benchmarks.
My Feedback:
First Phi 3, now OpenELM. It's great to see these small models improving. I know they're not ready for production in all cases, but they're really great for specific tasks.
I see small open-source models as the future because they offer better speed, require less compute, and use fewer resources, making them more accessible and practical for a wider range of applications.
What do you think about this? Do you consider using small opensource. If yes what you are thinking to make?
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[ 5.2 ms ] story [ 44.0 ms ] threadhttps://arxiv.org/abs/2404.14619
However, the model is proprietary. I'm tired of the open washing.
> 270M, 450M, 1.1B and 3B parameters
Which roughly translates to 3GB for the highest end one, depending on context length used.
8 bits = 1 byte
3 billion * 1 byte = 3 gigabyte
+ Some memory for the context of the LLM
[0]
3b-instruct has a total file size of 4.94GB + 1.13GB which is 6.07GB which can be seen here:
https://huggingface.co/apple/OpenELM-3B-Instruct/tree/main
A bit of overhead will always be there, as you probably want to store some metadata next to the raw weights.
OpenELM offers models with 270M to 3B parameters, pre-trained and instruction-tuned, with Good results across various benchmarks.
My Feedback:
First Phi 3, now OpenELM. It's great to see these small models improving. I know they're not ready for production in all cases, but they're really great for specific tasks.
I see small open-source models as the future because they offer better speed, require less compute, and use fewer resources, making them more accessible and practical for a wider range of applications.
What do you think about this? Do you consider using small opensource. If yes what you are thinking to make?
I am going to use it on my smartphone