|
b5d1456a09
|
backwards compat for my shitty old weights (was testing if disabling AudioEmbedding summing magically made things better (it did not))
|
2024-04-29 22:14:01 -05:00 |
|
|
6a11bc9cb6
|
update tokenizer because, for some reason, it had the wrong order for the special tokens to where eos = unk
|
2024-04-29 09:09:26 -05:00 |
|
|
57810e4ba4
|
metadata only path (might drop HDF5 since its giving file sizes twice as large as my actual unpacked dataset)
|
2024-04-28 23:03:09 -05:00 |
|
|
caad7ee3c9
|
final tweaks, hopefully
|
2024-04-28 22:28:29 -05:00 |
|
|
ffc334cf58
|
added dataset transcription helper script (now I don't ever have to touch ai-voice-cloning) (to-do: unify scripts into the module)
|
2024-04-21 17:43:20 -05:00 |
|
|
071fb97777
|
dataset preparation script updates, caved and am using HF tokenizer now
|
2024-04-21 14:49:18 -05:00 |
|
|
8214aa23d7
|
converting over to a different intermediary dataset format
|
2024-04-18 21:24:06 -05:00 |
|
|
4f5c9e518a
|
actually use the passed-through sample rate from encode for DAC because it does its own resampling I guess
|
2024-04-18 13:32:41 -05:00 |
|
|
545162195b
|
deprecate sole AR/NAR model by only keeping the AR+NAR (the beauty of no one using this is that I can break compat as much as I want), add tone token for when I classify my dataset with tone/emotion in the future, some other things
|
2024-04-15 19:54:32 -05:00 |
|
|
9c198eb75a
|
added torchscale XMOE integration (because Mixtral 8x7B seems very promising and I want to see if it works)
|
2023-12-20 18:45:58 -06:00 |
|
|
0aa2a3cc07
|
evaluation/validation passes language ID during training (oops)
|
2023-10-29 12:00:40 -05:00 |
|
|
9a6040383e
|
make validation samplers ignore sampler type
|
2023-10-22 09:01:47 -05:00 |
|
|
3195026dba
|
fixed issue with the 'add another target audio to artificially create longer sequences' for HDF5 just duplicating the utterance initially sampled
|
2023-10-18 20:38:33 -05:00 |
|
|
09cda7d3f9
|
added sampling by speaker group name (might be better to de-emphasize the LibriVox/Audiobooks that are in large numbers, and emphasize the smaller pools), log cleanup
|
2023-10-16 19:30:38 -05:00 |
|
|
65f500083d
|
tweaks to try and get deepspeed quantized inferencing, validating bitsandbytes and deepspeed quantization, nothing seems to work
|
2023-10-12 22:21:43 -05:00 |
|
|
8740cdefc6
|
added initial support for languages (still testing, marked as model version 3), added experimental 'context extend by limiting the resp context' (untested)
|
2023-10-11 20:38:40 -05:00 |
|
|
6045cbce94
|
added experimental option to append utterances for training target (emphasis on experimental)
|
2023-10-11 17:32:45 -05:00 |
|
|
b4405c98ea
|
remove double spaces in the text phonemes (might have caused problems.........)
|
2023-10-10 19:18:24 -05:00 |
|
|
87db03dd93
|
trim the input prompt to 3 seconds when training NAR tasks (marked as experimental; the paper mentions doing so, but I don't know how much this would harm the retention heads)
|
2023-10-09 22:03:58 -05:00 |
|
|
893a610fad
|
cleanup, use deepspeed inferencing pathway if requested
|
2023-10-09 15:24:04 -05:00 |
|
|
27483e56f0
|
disabled preparing of SpeechX tasks, added dynamic temperature testing (to-do: test it, credited in the function)
|
2023-10-09 13:01:40 -05:00 |
|
|
82f02ae9b1
|
oops
|
2023-10-06 09:26:52 -05:00 |
|
|
d12877ee09
|
added option to set probability of selecting the AR during training under a monolithic AR+NAR, added some more to-dos while I have them in mind
|
2023-10-02 16:52:42 -05:00 |
|
|
a6bfe43590
|
added mirostat sampling (given a partially trained model, it got far decent output than I expected, need to test on a better trained model)
|
2023-09-18 18:55:41 -05:00 |
|
|
d07c63b9d8
|
unified more things with training the AR+NAR monolothic model
|
2023-09-12 15:54:41 -05:00 |
|
|
40ef34e1ca
|
this embedding class definitely works, and migrating from the previous embedding weights seems to work.
|
2023-09-11 14:13:42 -05:00 |
|
|
8a6c203277
|
added per-speaker samplers
|
2023-09-03 21:27:13 -05:00 |
|
|
922404285c
|
fixed segfault from tts-c task token exceeding being too big (inserted it in the hypothetical svc task token because in reality that is never ever going to be a feasible task to train against)
|
2023-09-02 19:25:43 -05:00 |
|
|
4613781e23
|
integrated plot script, added tts-c task token to help the model be able to mix between normal VALL-E and VALL-E continuous
|
2023-09-02 16:29:53 -05:00 |
|
|
71e68a8528
|
tweaked tts-continuous task
|
2023-09-02 13:39:17 -05:00 |
|
|
57db3ccfa8
|
shuffled VALL-E continuous as a task tts-c instead, logic fixes for it
|
2023-09-02 12:23:40 -05:00 |
|
|
2bc2d08b09
|
(need to verify) added modifying model size and config bool to align with VALL-E continuous' methodology
|
2023-09-01 17:19:34 -05:00 |
|
|
5c8694db8e
|
nasty bandaid if there's no validation dataset specified during training (for example, during finetunes)
|
2023-08-30 18:23:05 -05:00 |
|
|
7f4388e591
|
added total samples processed and tokens processed (len of text tokens + len of target response tokens)
|
2023-08-28 11:02:45 -05:00 |
|
|
87c4bfedba
|
added ability to mark models as disabled for training, and hotloading them for eval/validation (useful if training only one model, or training a model per GPU)
|
2023-08-27 12:26:12 -05:00 |
|
|
165a1154e0
|
Undo naive=False test flag, this shouldn't have made its way in
|
2023-08-26 22:00:43 -05:00 |
|
|
78378ed1ce
|
overhauled dataloading code to be marginally faster, mostly cleaned up, and can leverage a metadata json to help things out
|
2023-08-26 19:53:23 -05:00 |
|
|
0517d620b8
|
fixes with the local backend
|
2023-08-24 17:05:56 -05:00 |
|
|
22904a8639
|
more oversights fixed because I've been using a cached dataloader forever now and didn't catch these problems
|
2023-08-24 10:25:33 -05:00 |
|
|
5873c27f1a
|
ops
|
2023-08-24 09:20:47 -05:00 |
|
|
4585824cd3
|
tweaks, including exporting on save/quit
|
2023-08-23 16:43:03 -05:00 |
|
|
9c5a33bfd2
|
added repo with my weights so far
|
2023-08-22 13:09:44 -05:00 |
|
|
7b1b82e0e5
|
inferencing cleanup
|
2023-08-20 21:36:02 -05:00 |
|
|
a47029065b
|
I don't know if the lack of start/stop tokens being added was causing my inference tests to fail, but it seems better now
|
2023-08-20 19:21:54 -05:00 |
|
|
fc576010ce
|
wrapped saving the checkpoint in a try/catch so I can stop waking up to the damn trainer crashing because it ran out of disk space; I'd much rather it keep training to give me time to eventually clear up disk space rather than it silently restarting on its own
|
2023-08-20 06:29:17 -05:00 |
|
|
2d1a9f10c0
|
nightmare of spaghetti that might break compat; mechanism to increase RVQ bins of an existing model without retraining, keeps sampled proms/resps at max RVQ level and trim off excess levels according to what model receives them, some other things I already forgot (I really hope no one else has weights being baked right now)
|
2023-08-19 15:06:33 -05:00 |
|
|
f7f6d3bf6d
|
validated that SpeechX tasks cse and nse works, added a method to test each task by invoking python3 -m vall_e.data --action=tasks --tasks='sr,se,cse,nse'
|
2023-08-19 09:50:07 -05:00 |
|
|
6ca347e1e1
|
literally had a urethra moment before going to bed with a way to implement cse/nse tasks
|
2023-08-19 01:16:46 -05:00 |
|
|
8f42c578c9
|
setting up for allowing training for a partial amount of the speechx tasks (do NOT try this at home yet without a proper model, as performance is predecated on having a solid base vall-e model for the tasks
|
2023-08-19 00:16:08 -05:00 |
|
|
ae9d38aa31
|
forgot to have it pull from specified noise to the hdf5 dataset
|
2023-08-18 23:57:07 -05:00 |
|