|
|
95da4e9405
|
made muon actually work by actually utilizing param groups (thanks APOLLO for reminding me this is the sane way to handle this split)
|
2025-02-26 10:39:13 -06:00 |
|
|
|
cbf6b84e27
|
fixed grad norm and loss scale not reporting for local trainer
|
2025-02-23 19:08:26 -06:00 |
|
|
|
b640fabab5
|
borrowed muon since it might better work under deepspeed and not require cruft (even though it really does not like the masked-NAR, also make the masked-NAR faux-causal since it might better help out for cfg.model.version >= 7
|
2025-02-23 17:23:24 -06:00 |
|
|
|
3019c88799
|
separate mask token and stop token because this might cause issues
|
2025-02-23 11:36:32 -06:00 |
|
|
|
6634d07576
|
added muon optimizer through kludge hacks because it necessitates a second optimizer in tandum that seems to only sometimes work with deepspeed
|
2025-02-23 11:22:13 -06:00 |
|
|
|
a65c8144f4
|
with the amount of tweaks I keep making I could have probably had the nvidia/audio-codec-44khz model realized already......
|
2025-02-13 18:38:40 -06:00 |
|
|
|
d4a6709fb4
|
stopgap cringe to get this training session working (it does not seem fruitful)
|
2025-02-11 13:45:09 -06:00 |
|
|
|
353e478e68
|
agony
|
2024-12-21 22:52:10 -06:00 |
|
|
|
d85273609e
|
corrected export.py's --hf
|
2024-12-20 15:17:13 -06:00 |
|
|
|
c2c6d912ac
|
actually do speaker verification
|
2024-12-17 10:11:14 -06:00 |
|
|
|
8515038968
|
imagine my disappointment when the epoch finished just for it to throw an exception
|
2024-12-16 18:28:01 -06:00 |
|
|
|
2ba6b483dc
|
ugh
|
2024-12-14 22:43:51 -06:00 |
|
|
|
3dd31e74d1
|
finally figured out a clean way to handle "resuming" the tqdm bar
|
2024-12-14 18:44:43 -06:00 |
|
|
|
35389481ee
|
move lazy-stored ortho matrix to the grad device for apollo because agony
|
2024-12-13 23:22:26 -06:00 |
|
|
|
09804ecc16
|
APOLLO tweaks to make it work with deepspeed
|
2024-12-13 23:03:52 -06:00 |
|
|
|
64c67160a3
|
tweaks
|
2024-12-13 19:00:35 -06:00 |
|
|
|
f41251f648
|
more fixes for local engine backend
|
2024-12-12 14:38:42 -06:00 |
|
|
|
9a62e3b824
|
APOLLO cringe (doesn't want to work with deepspeed)
|
2024-12-12 00:31:58 -06:00 |
|
|
|
b81a98799b
|
uplifting transformer's WavLM stuff to do speaker verification instead
|
2024-12-11 19:30:05 -06:00 |
|
|
|
6f1ee0c6fa
|
Added CER, transcription/similarity model args in demo
|
2024-12-10 21:00:51 -06:00 |
|
|
|
8568a93dad
|
added WER/SIM-O metrics, added APOLLO but I need to test it
|
2024-12-10 20:13:21 -06:00 |
|
|
|
34a66e1052
|
agnostified KD
|
2024-12-06 23:53:46 -06:00 |
|
|
|
42fafbaaca
|
actually fixed knowledge distillation because of errant -inf logits causing problems and needed to be filtered (and splitting text language / output audio language because it helps)
|
2024-12-06 21:55:20 -06:00 |
|
|
|
dcaf38b359
|
fixed training tqdm being stubborn
|
2024-11-23 09:45:23 -06:00 |
|
|
|
88d840218d
|
default set cfg strength to 3.0 since the reference model is updated
|
2024-11-17 10:23:40 -06:00 |
|
|
|
29e45be0b4
|
tweaks to bucket sampling
|
2024-11-13 11:09:24 -06:00 |
|
|
|
b2eca271a8
|
ugh
|
2024-11-13 10:35:44 -06:00 |
|
|
|
ad7cfffc00
|
NAR-len RVQ-0 was being trained causally.............
|
2024-11-13 09:43:50 -06:00 |
|
|
|
976ee87f6f
|
resume iteration step in tqdm trainer, warn to logger if the sampler state dict was invalidated
|
2024-11-13 09:09:28 -06:00 |
|
|
|
0f2584eba7
|
new meme sampler PogChamp new meme sampler PogChamp (it sort of helps?)
|
2024-11-12 22:30:09 -06:00 |
|
|
|
2f56696506
|
overhauled inference/sampler kwargs to stop being a bloated mess
|
2024-11-11 20:21:16 -06:00 |
|
|
|
354f8e059d
|
store dataset hash alongside state dict so it can be ignored if mismatched
|
2024-11-11 18:16:56 -06:00 |
|
|
|
f7b8b1e825
|
dropped subtrain dataloader since its useless to duplicate
|
2024-11-11 17:00:49 -06:00 |
|
|
|
cf9df71f2c
|
use homwbrewed caching system for dataloader paths / durations (I'm pretty sure I am now triggering OOM killers with my entire dataset used)
|
2024-11-11 16:32:08 -06:00 |
|
|
|
a9d2faf2d7
|
all I can do now until I wait for the model to (re)train for pure NAR
|
2024-11-09 22:57:34 -06:00 |
|
|
|
8eb9a4056b
|
modified default arguments (ar temp = 0 and rep pen = 1.125 seems to be stable, at least given the few things i tested), do not pass top k/top p/min p to NAR even though technically none of those things should matter when greedy sampling
|
2024-10-22 18:12:39 -05:00 |
|
|
|
fc8dfd8617
|
made greedy AR sampling viable (and preferable), with caveats (per comment in vall_e.models.ar_nar)
|
2024-10-18 16:55:00 -05:00 |
|
|
|
75b90be325
|
cleaned up unused config flags, allow less strict yaml by pruning missing keys, renamed some dataset configs to be more unified
|
2024-10-17 17:06:48 -05:00 |
|
|
|
a507b769a1
|
sped up inferencing by not doing .tolist() for rep pen / length pen (and a bug fix in the web UI from prev commit)
|
2024-10-04 22:18:20 -05:00 |
|
|
|
769f67dcfe
|
actually fix validation of phonemes in the symmap
|
2024-09-21 12:19:34 -05:00 |
|
|
|
b5bec0c9ce
|
oops, turns out these are not split by speaker names already........ (also added sampling the dataset in the webui for easy viewing)
|
2024-09-18 20:19:46 -05:00 |
|
|
|
84647f588a
|
more tweaks
|
2024-09-18 16:43:57 -05:00 |
|
|
|
ebac1db16c
|
maybe final tweaks, I really needed to unify my json read/write and orjson is proven to be fast enough for me to try and rely on it more
|
2024-09-17 22:57:04 -05:00 |
|
|
|
a9fbe81f98
|
oops
|
2024-09-17 15:25:12 -05:00 |
|
|
|
94cf81d38c
|
tweak
|
2024-09-05 23:21:18 -05:00 |
|
|
|
32287710a2
|
moved prints to use logger, edited readme (fused_attn doesnt seem stable for training)
|
2024-08-29 13:27:16 -05:00 |
|
|
|
3a65cc4b22
|
fix issue with sft and shared tensors...
|
2024-08-04 19:56:21 -05:00 |
|
|
|
2cb465018b
|
implicitly load either normal pickled weights or safetensors on loading the model
|
2024-08-03 23:34:18 -05:00 |
|
|
|
c09133d00f
|
added safetensors support (with metadata) and feed whatever torch.load/torch.save into it
|
2024-08-03 23:15:20 -05:00 |
|
|
|
6a733eb2ed
|
changed torch.Tensor().to(device, dtype) to just torch.tensor(..., device, dtype) because it's been bothering my autism that I'm creating tensors then converting rather than creating with the right device/dtype, some 'optimization' to compile the model but it doesnt seem to do anything useful
|
2024-08-03 22:10:21 -05:00 |
|
