mrq
-
https://git.ecker.tech/ aims to provide a place to share my efforts while maintaining true ownership of my code, as I do not trust GitHub.
XMR: 4B9TQdkAkBFYrbj5ztvTx89e5LpucPeTSPzemCihdDi9EBnx7btn8RDNZTBz2zihWsjMnDkzn5As1LU6gLv3KQy8BLsZ8SG
- Joined on
2022-10-10
Block a user
fc1ec2019d
added option to buffer process jobs across multiple speakers to maybe squeeze out some throughput speeds for vall_e.emb.process (in the event of lots of speakers with low file counts, such as Emilia)
92139b6da9
additional cruft, added a note in documentation to be aware of NUMA node topology when running vall_e.emb.process with more than one process
596c2df11c
added arg to skip processing speakers with not enough utterances for whenever I get around to processing my subest of Emilia for nvidia/audio-codec-44khz (because Emilia has a ton of low-utternace speaker counts and right now my focus with the nemo model is on getting it to actually speak without much problems rather than feed it a gorillion speakers)
8331eee6fa
added arg to limit vall_e.emb.process batch size since there's some speaker groups in LibriLight/Speech/whatever that have 10K utterances and I'm going impatient
dbcab9e570
added arg to limit vall_e.emb.process batch size since there's some speaker groups in LibriLight/Speech/whatever that have 10K utterances and I'm going impatient
6bc61c1a0f
added arg to limit vall_e.emb.process batch size since there's some speaker groups in LibriLight/Speech/whatever that have 10K utterances and I'm going impatient
8f86cf0e4e
possible logic optimization so I don't spend another 15 minutes simply iterating back to the point I was at in vall_e.emb.process
0dc49ef4d5
documentation update while I wait for more audio (between 4 and 8 seconds per utterance) quantize for nvidia/audio-codec-44khz (I was foolish to think I can get something servicable with just 4 seconds max for an utterance)
a65c8144f4
with the amount of tweaks I keep making I could have probably had the nvidia/audio-codec-44khz model realized already......