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a9d2faf2d7
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all I can do now until I wait for the model to (re)train for pure NAR
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2024-11-09 22:57:34 -06:00 |
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ad7e290a5e
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ugh (ROCm seems to silently clamp any token value >= logits.shape[-1] for loss calculation, while cuda will throw an assert, making it hard to find this dumb fuckup)
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2024-11-09 19:40:02 -06:00 |
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943fe70c10
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I don't know why this fixes an assert thrown but it does
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2024-11-09 19:04:13 -06:00 |
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f50d92ba6c
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Almost made a mistake
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2024-11-09 18:12:54 -06:00 |
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c6a38693a2
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This better work
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2024-11-09 18:04:59 -06:00 |
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8b3d1cf70a
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Something's Wrong
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2024-11-09 15:07:43 -06:00 |
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dcd5fecff3
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some cleanup while I wait for the NAR-len to train to an acceptable state (currently it performs okay, but only on audo after 3 seconds or so)
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2024-11-09 12:12:46 -06:00 |
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69b0b3b854
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set timestep tensor to whatever the time embedding's dtype is because it'll gripe under amp
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2024-11-09 00:11:16 -06:00 |
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5a09a5f6e9
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I forgot about the time embedding...
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2024-11-08 22:46:26 -06:00 |
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811b15d280
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I suppose I just have a shit training method since the sampler is as solid as I can get it...............
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2024-11-08 22:05:41 -06:00 |
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13b54953bd
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agony
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2024-11-08 13:34:39 -06:00 |
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c127c4e488
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'borrowed' a sampling scheduler for NAR-len's RVQ level 0 (better than before, but still not good enough)
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2024-11-07 21:19:14 -06:00 |
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e108c54daf
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new NAR-len training paradigm......
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2024-11-07 11:32:11 -06:00 |
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ed174c589e
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ugh
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2024-11-07 09:19:21 -06:00 |
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d13ab00ad8
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one more note
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2024-11-07 09:11:21 -06:00 |
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5698188824
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あたしって、ほんとバカ
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2024-11-07 09:10:18 -06:00 |
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77ff23e319
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repeat extend the prom to fill the initial tokens for nar-len (it somewhat works, the model just needs to train more)
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2024-11-06 23:29:53 -06:00 |
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a3bc26f7ec
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ugh
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2024-11-06 23:16:28 -06:00 |
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d606a693ff
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eval fix for nar-len
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2024-11-06 23:14:16 -06:00 |
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105ed51159
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I guess I'll fall for the NAR-len meme again (I don't know where my previous weights are, so I need to train it again to test something)
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2024-11-06 19:17:12 -06:00 |
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bcabde3454
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more notes
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2024-11-06 13:51:28 -06:00 |
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bfc5e1d723
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agony
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2024-11-05 22:30:49 -06:00 |
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aefe8fcdad
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UGH
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2024-11-05 22:13:58 -06:00 |
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556d9db0d5
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web UI support for HF ZeroGPU
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2024-11-05 21:38:02 -06:00 |
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e58a9469a3
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move layerskip to experimental settings.......
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2024-11-05 20:37:06 -06:00 |
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bbc2de3713
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ugh
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2024-11-05 11:50:05 -06:00 |
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9e65e05e83
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more windows specific fixes, limit gradio to <5.0.0 on linux (it works on windows, but not on my linux machine tm)
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2024-11-04 18:00:33 -06:00 |
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c83670c38c
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Windows specific fixes (to-do: find libespeak-ng.dll automatically because it cannot be trusted to do it by default)
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2024-11-03 19:19:15 -06:00 |
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d229725c76
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more adjustments (adjustments of early-exit entropy/varentropy thresholds, default rep pen being 1.5, experimental refine-on-stop, etc.)
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2024-11-03 18:31:28 -06:00 |
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aee08b7307
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changed layerskip float16 training warning (since it didnt seem to fry on my 4xV100 system)
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2024-11-03 09:58:29 -06:00 |
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3826f9bae4
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saner mask creation? (it doesnt matter, kv cache wont work)
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2024-11-02 21:00:21 -05:00 |
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ded746e157
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very, very naive layerskip speculative sampling (it just checks if the current layer's state is good enough)
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2024-11-02 11:49:05 -05:00 |
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62fe5b0943
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ughh
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2024-11-01 22:36:48 -05:00 |
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ec79230965
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shuffled web UI options hidden by cfg.experimental to its own tab, expose early exit selection to inferencing (it kinda works naively, still need to implement self-speculation)
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2024-11-01 21:30:06 -05:00 |
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ef1c17430f
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skip step on nan loss (ironically I have not had a nan loss after adding this), throw exception with invalid cfg.dataset.sample_type and sample_order combination (because I was tricked by this in my yaml and had inconsistent vram usage)
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2024-11-01 20:54:53 -05:00 |
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fb8faa295b
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actually float16(+AMP) and layerskip is bad and will kill the model......
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2024-11-01 18:36:44 -05:00 |
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edf1e66bf9
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layerskip_r=6 fries the model so hard the loss is sub-1...
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2024-11-01 17:06:07 -05:00 |
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9b6c57bc57
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third time's the charm (for some reason it escaped me that I should treat early exit loss as an aux_loss to be used with the normal loss, as if I was training a MoE's router)
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2024-11-01 12:50:37 -05:00 |
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76ebef45dc
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off-by-one...
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2024-10-31 13:24:48 -05:00 |
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b63293cbbe
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ugh
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2024-10-30 22:49:11 -05:00 |
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a22534e8f4
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layer skip training implemented (need to gut the inferencing from the repo, and to actually see if the model can benefit from this)
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2024-10-30 20:05:45 -05:00 |
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4049f51ba9
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added option to load lora directly from the model file itself with --lora
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2024-10-26 00:13:10 -05:00 |
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ccf71dc1b6
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added option to load from a model state dict directly instead of a yaml (to-do: do this for LoRAs too), automatically download the default model if none is provided
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2024-10-25 22:15:15 -05:00 |
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a96f5aee32
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adjusted how i want to pass eval kwargs
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2024-10-25 20:38:09 -05:00 |
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92e6bff6dc
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actually ar temp 0.5 with rep pen 1.125 seems to have the benefits of better outputs without it degrading some of the time but not all the time
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2024-10-23 00:03:35 -05:00 |
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8920e5e86b
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actually have beam_width in the webUI work
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2024-10-22 22:06:22 -05:00 |
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910571ad34
|
too brainlet to diagnose why low temp / greedy sampling is randomly unstable some of the time
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2024-10-22 20:13:54 -05:00 |
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8eb9a4056b
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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
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2024-10-22 18:12:39 -05:00 |
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1a02cd5bce
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modify demo template to say F5 instead of YourTTS, swap LoRA comparison around to make the lora'd the base file, and the no-lora the suffix'd file
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2024-10-21 19:52:02 -05:00 |
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02dfc60ac3
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ugh
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2024-10-18 17:23:22 -05:00 |
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71731ed785
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added prefixing with silence (was to test something, currently hidden under cfg.experimental=True)
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2024-10-18 17:19:52 -05:00 |
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6b04c13c56
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print warning if audio promtpless inferencing with low AR temp (it really doesn't like low temps / greedy sampling)
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2024-10-18 17:01:40 -05:00 |
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c8f31db1de
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default to greedy sample AR (i should probably test this more but it seems to pass my harvard sentences and tongue twisters)
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2024-10-18 16:58:56 -05:00 |
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fc8dfd8617
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made greedy AR sampling viable (and preferable), with caveats (per comment in vall_e.models.ar_nar)
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2024-10-18 16:55:00 -05:00 |
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07f4935a75
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more tweaks
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2024-10-18 13:19:36 -05:00 |
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0dfab973e7
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oops
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2024-10-18 09:40:06 -05:00 |
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75b90be325
|
cleaned up unused config flags, allow less strict yaml by pruning missing keys, renamed some dataset configs to be more unified
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2024-10-17 17:06:48 -05:00 |
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8b6095f681
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saner defaults, maybe
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2024-10-17 14:37:21 -05:00 |
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f88097ccf6
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add config option to set the rate of sampling randomly vs similar speakers during training
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2024-10-16 14:27:58 -05:00 |
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48461833c2
|
ugh
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2024-10-15 19:30:43 -05:00 |
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eea70f5698
|
kludge fix for an oversight in the model when trying to train for longer input prompt durations......
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2024-10-15 19:25:03 -05:00 |
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84005c5b00
|
entropix apparently processes the entire sequence of logits but it falls apart when doing that
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2024-10-13 12:01:12 -05:00 |
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c800d28bb8
|
respect attention defined in the yaml for web UI (which might explain why theres been a discrepancy in outputs for me)
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2024-10-13 11:02:24 -05:00 |
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ed6b7a690f
|
ugh.........
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2024-10-13 00:26:46 -05:00 |
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d405f243d4
|
at wits end in trying to output the right attention scores
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2024-10-12 23:53:13 -05:00 |
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70cf694cfd
|
output attention scores for SDPA/flash, since naive attention seems broken
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2024-10-12 12:09:17 -05:00 |
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541e45263c
|
ugh
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2024-10-12 11:29:16 -05:00 |
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04e983b86b
|
modified demo page to be more modular with demoing comparisons, actually provide a path to use modified naive attention, entropix sampling is not tied to an experimental yaml flag now
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2024-10-12 11:27:55 -05:00 |
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666e8038fb
|
ugh
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2024-10-12 10:41:35 -05:00 |
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3d6ef9666b
|
overridden naive llama attention to get the right score values that entropix needs
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2024-10-12 10:05:47 -05:00 |
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40b089daf3
|
lol
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2024-10-12 09:57:34 -05:00 |
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d6f7c86a5c
|
entropix tweaks (it doesn't output garbage but it loves to go for silence)
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2024-10-12 09:46:18 -05:00 |
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d0ab7d755a
|
added min-p (really does not seem useful since it's very sensitive), more tweaks to entropix
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2024-10-11 22:36:06 -05:00 |
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bef43a0c18
|
added experimental entropix sampling support
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2024-10-11 21:18:26 -05:00 |
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85d85c1351
|
more arg creep for demo page
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2024-10-10 19:40:01 -05:00 |
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301468f519
|
<<
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2024-10-10 19:13:52 -05:00 |
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75a4c866d6
|
more demo page tweaks, added arg to force enable/disable LoRAs for inferencing (to-do: setup arg flags to handle this, and checkbox in web UI)
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2024-10-10 19:04:12 -05:00 |
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96d05be73c
|
demo page tweaks
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2024-10-10 13:52:37 -05:00 |
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2ea978f318
|
added --eval-random-text-prompts to use random text prompts for eval pass, added --random-prompts for demo page and --lora to use a sample with the lora disabled, probably finally fixed validation dataloader breaking on eval
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2024-10-10 13:40:25 -05:00 |
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52299127ab
|
fix vall_e.emb.process
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2024-10-08 20:00:34 -05:00 |
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0656a762af
|
fix vall_e.emb.transcriber
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2024-10-08 19:24:43 -05:00 |
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acdce66d4e
|
readme tweaks, set the (unused) default model download URL back to the base ar+nar-llama-8 model, as ar+nar-tts+stt-llama-8 was renamed back to it since it performs well
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2024-10-05 22:53:53 -05:00 |
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84c7419001
|
faster
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2024-10-04 22:30:47 -05:00 |
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a507b769a1
|
sped up inferencing by not doing .tolist() for rep pen / length pen (and a bug fix in the web UI from prev commit)
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2024-10-04 22:18:20 -05:00 |
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4a8e3ccf06
|
README tweaks, added --input-prompt-prefix as an experiment (its literally better to just not do this, but i'll retain it in case i have a revelation on how to improve it)
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2024-10-04 18:57:19 -05:00 |
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a9fa0898a9
|
tweaked demo page script to sample speakers instead
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2024-09-28 10:50:26 -05:00 |
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2f1dca3089
|
added language selection in web UI, tweaked demo script
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2024-09-28 09:49:45 -05:00 |
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10df2ef5f3
|
fixed oversight where input audio does not resample (lol...)
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2024-09-27 20:27:53 -05:00 |
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039482a48e
|
don't do eval on stt because it's so slow and I don't even bother doing any metrics against it anyways (to-do: make this a flag)
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2024-09-26 18:56:57 -05:00 |
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ff7a1b4163
|
coerce into path for other sampler_types (it's required for sampling for similar utterances)
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2024-09-26 18:37:56 -05:00 |
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f24547ad4e
|
add top_k sampling / offset for prompt similar utterance sampling
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2024-09-26 16:26:40 -05:00 |
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9da630f73a
|
swap order of demo entries, as the model prioritizes adhering to the speaker prompt more (instead of trying to match the ground truth magically)
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2024-09-25 23:31:24 -05:00 |
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e84d466261
|
vall_e.plot tweaks
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2024-09-24 20:05:10 -05:00 |
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c5e9142863
|
added option to retokenize phonemes for hdf5 (to save having to remake my hdf5 file)
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2024-09-21 13:08:01 -05:00 |
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536c11c4ac
|
actually validated and fixed sampling similar utterances for the prompt (hopefully nothing else is needed)
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2024-09-21 12:59:51 -05:00 |
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d31f27119a
|
regex replace out the (lang) markers in espeak, updated tokenizer vocab as lazily as possible to not have unk tokens
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2024-09-21 12:29:28 -05:00 |
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769f67dcfe
|
actually fix validation of phonemes in the symmap
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2024-09-21 12:19:34 -05:00 |
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c8d4716a9f
|
ugh
|
2024-09-18 21:40:57 -05:00 |
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fe241f6a99
|
support for wildcard in training/validation/noise dataset array (to-do: a better way to query between metadata folder and data folder)
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2024-09-18 21:34:43 -05:00 |
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b5bec0c9ce
|
oops, turns out these are not split by speaker names already........ (also added sampling the dataset in the webui for easy viewing)
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2024-09-18 20:19:46 -05:00 |
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