time to first audio is something that is crucial for us to reduce the latency - wondering if dia works with output streaming?
the python code snippet seems to imply that the entire audio bytes are generated directly?
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time to first audio is something that is crucial for us to reduce the latency - wondering if dia works with output streaming?
the python code snippet seems to imply that the entire audio bytes are generated directly?
Impressive demo! We'd love to use this at https://useponder.ai time to first audio is something that is crucial for us to reduce the latency - wondering if dia works with output streaming? the python code snippet seems to imply that the entire audio bytes are generated directly?
It's way past bedtime where I live, so will be able to get back to you after a few hours. Thanks for the interest :)
Darn, don't have the appropriate hardware. The full version of Dia requires around 10GB of VRAM to run. If you have a 16gb of VRAM, I guess you could pair this with a 3B param model along side it, or really probably only 1B param with reasonable context window.
We've seen Bark from Suno go from 16GB requirement -> 4GB requirement + running on CPUs. Won't be too hard, just need some time to work on it.
Impressive demo! We'd love to use this at https://useponder.ai time to first audio is something that is crucial for us to reduce the latency - wondering if dia works with output streaming? the python code snippet seems to imply that the entire audio bytes are generated directly?
Sounds awesome! I think it won't be very hard to run it using output streaming, although that might require beefier GPUs. Give us an email and we can talk more - nari.ai.contact at gmail dot com. It's way past bedtime where I live, so will be able to get back to you after a few hours. Thanks for the interest :)
Darn, don't have the appropriate hardware. The full version of Dia requires around 10GB of VRAM to run. If you have a 16gb of VRAM, I guess you could pair this with a 3B param model along side it, or really probably only 1B param with reasonable context window.
We will work on a quantized version of the model, so hopefully you will be able to run it soon! We've seen Bark from Suno go from 16GB requirement -> 4GB requirement + running on CPUs. Won't be too hard, just need some time to work on it.
Impressive! Is it english only at the moment?
How do you declare which voice should be used for a particular speaker? And can it created a cloned speaker voice from a sample?