* https://docs.rs/sanakirja-core
* https://pijul.org/posts/2021-02-06-rethinking-sanakirja#benc...
517 karma · joined October 10, 2017
* https://docs.rs/sanakirja-core
* https://pijul.org/posts/2021-02-06-rethinking-sanakirja#benc...
https://delta.chat/en/help#can-i-use-a-classic-email-address...
Sprinkled with a little bit of https://delta.chat ?
And potentially a dash of iroh https://news.ycombinator.com/item?id=48542480 https://www.iroh.computer/solutions/delta-chat ?
https://machinelearning.apple.com/research/introducing-third...
"That’s where EMO comes in.
We show that EMO – a 1B-active, 14B-total-parameter (8-expert active, 128-expert total) MoE trained on 1 trillion tokens – supports selective expert use: for a given task or domain, we can use only a small subset of experts (just 12.5% of total experts) while retaining near full-model performance."
https://allenai.org/blog/emoThey use a technique where you only load between 1B and 4B of a 20B dense model for an entire prompt run, not token by token like a MoE, and use mostly the low power ANE instead of GPU cores.
Now, imagine if/when they scale up to 100B or more? On a chip using 2W?
We show that EMO – a 1B-active, 14B-total-parameter (8-expert active, 128-expert total) MoE trained on 1 trillion tokens – supports selective expert use: for a given task or domain, we can use only a small subset of experts (just 12.5% of total experts) while retaining near full-model performance."
I thought you were talking about this: https://www.youtube.com/watch?v=6OGvj7GZSIo
Weights, datasets, code, multiple checkpoints...
I like their FlexOlmo concept.
Not
"Train from scratch"
They are talking about this kind of battery replacement: https://www.ifixit.com/Guide/Fairphone+3+Battery+Replacement... . The "TV remote" battery replacement kind.
edit: and for the current unfortunately there's only a dead dropbox link.