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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
|
ugh
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2024-11-05 11:50:05 -06:00 |
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9e65e05e83
|
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
|
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
|
off-by-one...
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2024-10-31 13:24:48 -05:00 |
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b63293cbbe
|
ugh
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2024-10-30 22:49:11 -05:00 |
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a22534e8f4
|
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
|
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
|
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
|
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
|
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
|
2024-10-23 00:03:35 -05:00 |
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8920e5e86b
|
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
|
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
|
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
|
ugh
|
2024-10-18 17:23:22 -05:00 |
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71731ed785
|
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
|
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
|
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
|
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
|
more tweaks
|
2024-10-18 13:19:36 -05:00 |
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|
0dfab973e7
|
oops
|
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
|
2024-10-17 17:06:48 -05:00 |
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8b6095f681
|
saner defaults, maybe
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2024-10-17 14:37:21 -05:00 |
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f88097ccf6
|
add config option to set the rate of sampling randomly vs similar speakers during training
|
2024-10-16 14:27:58 -05:00 |
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|
48461833c2
|
ugh
|
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......
|
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
|
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)
|
2024-10-13 11:02:24 -05:00 |
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ed6b7a690f
|
ugh.........
|
2024-10-13 00:26:46 -05:00 |
|
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|
d405f243d4
|
at wits end in trying to output the right attention scores
|
2024-10-12 23:53:13 -05:00 |
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70cf694cfd
|
output attention scores for SDPA/flash, since naive attention seems broken
|
2024-10-12 12:09:17 -05:00 |
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|
541e45263c
|
ugh
|
2024-10-12 11:29:16 -05:00 |
|
|
|
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
|
2024-10-12 11:27:55 -05:00 |
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|
|
666e8038fb
|
ugh
|
2024-10-12 10:41:35 -05:00 |
|
|
|
3d6ef9666b
|
overridden naive llama attention to get the right score values that entropix needs
|
2024-10-12 10:05:47 -05:00 |
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|
40b089daf3
|
lol
|
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)
|
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
|
2024-10-11 22:36:06 -05:00 |
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bef43a0c18
|
added experimental entropix sampling support
|
2024-10-11 21:18:26 -05:00 |
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85d85c1351
|
more arg creep for demo page
|
2024-10-10 19:40:01 -05:00 |
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|
301468f519
|
<<
|
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)
|
2024-10-10 19:04:12 -05:00 |
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96d05be73c
|
demo page tweaks
|
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
|
2024-10-10 13:40:25 -05:00 |
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|
52299127ab
|
fix vall_e.emb.process
|
2024-10-08 20:00:34 -05:00 |
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0656a762af
|
fix vall_e.emb.transcriber
|
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
|
2024-10-05 22:53:53 -05:00 |
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84c7419001
|
faster
|
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)
|
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)
|
2024-10-04 18:57:19 -05:00 |
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a9fa0898a9
|
tweaked demo page script to sample speakers instead
|
2024-09-28 10:50:26 -05:00 |
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2f1dca3089
|
added language selection in web UI, tweaked demo script
|
2024-09-28 09:49:45 -05:00 |
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|
10df2ef5f3
|
fixed oversight where input audio does not resample (lol...)
|
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)
|
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
|
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)
|
2024-09-25 23:31:24 -05:00 |
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|
e84d466261
|
vall_e.plot tweaks
|
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)
|
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)
|
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
|
2024-09-21 12:29:28 -05:00 |
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769f67dcfe
|
actually fix validation of phonemes in the symmap
|
2024-09-21 12:19:34 -05:00 |
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|
|
c8d4716a9f
|
ugh
|
2024-09-18 21:40:57 -05:00 |
|
|
|
fe241f6a99
|
support for wildcard in training/validation/noise dataset array (to-do: a better way to query between metadata folder and data folder)
|
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)
|
2024-09-18 20:19:46 -05:00 |
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|
fa9d3f6c06
|
lang fixes / reworked phoneme symmap validation
|
2024-09-18 19:36:03 -05:00 |
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|
84647f588a
|
more tweaks
|
2024-09-18 16:43:57 -05:00 |
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|
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 |
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|
6ceed866b5
|
*faster*
|
2024-09-17 22:44:36 -05:00 |
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|
f00283440c
|
faster
|
2024-09-17 22:26:31 -05:00 |
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|
be22b65300
|
solved my problem
|
2024-09-17 21:58:44 -05:00 |
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|
8f41d1b324
|
more tweaks
|
2024-09-17 16:26:30 -05:00 |
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804ddb5182
|
optimizations (6 hours to do cosine similarities on a speaker set of just 17k utterances................)
|
2024-09-17 15:51:45 -05:00 |
|
|
|
a9fbe81f98
|
oops
|
2024-09-17 15:25:12 -05:00 |
|
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|
c440c4fe7e
|
relegated processing similarity data into vall_e.emb.similarity since it's easier, seems to work?
|
2024-09-17 14:37:21 -05:00 |
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56f25f7a9b
|
more stuff for similar-speaker prompt sampling (to-do: actually test if this works...)
|
2024-09-16 23:10:29 -05:00 |
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|
69f140ba45
|
fix oversight with phonemizing french because espeak defines french as fr-fr instead of fr (even though spain spanish is es and not es-sp or some shit, but portugal portuguese is pt-pt)
|
2024-09-13 12:53:36 -05:00 |
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4f3c7a37c8
|
also do text similarities (dont know what use I'll have for this)
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2024-09-10 16:45:59 -05:00 |
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1c615a0f52
|
helper script (vall_e.emb.similar) to figure out the best way to compute similarity scores for audio (iunno how to go about it desu)
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2024-09-10 16:34:23 -05:00 |
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d059f6f56d
|
added helper script to process Emilia (amphion/Emilia-Dataset), clean up espeak phonemes for non-English transcriptions with English words (because for some reason espeak injects (en){word}(lang) markers and it's annoying)
|
2024-09-09 09:57:32 -05:00 |
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|
31e8b7edb8
|
tweaks and fixes for lora stuffs
|
2024-09-08 18:05:21 -05:00 |
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|
54203c059d
|
validated rep pen for STT (sometimes needed to wrangle the model)
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2024-09-08 08:30:30 -05:00 |
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6a967f91b9
|
oops
|
2024-09-07 22:13:49 -05:00 |
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|
5d66a7db52
|
webui cleanup, more tweaks, default to safetensors in config
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2024-09-07 21:45:05 -05:00 |
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|
a6ad0577b8
|
cleanup the resultant text from STT
|
2024-09-06 18:44:25 -05:00 |
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fa93061b3e
|
more fixes, moved sampler state dict to a better place, eval works again
|
2024-09-06 16:59:56 -05:00 |
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4bd9bb39c8
|
webui for STT (still need to bake the model to handle it better, a few hours so far has it generate what looks like a normal transcription but does not correlate to the audio right now)
|
2024-09-06 15:13:04 -05:00 |
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d33a906119
|
cleanup for AR_NAR inferencing to allow both TTS and STT tasks simultaneously (need to have training eval do this to though)
|
2024-09-06 14:30:12 -05:00 |
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|
341e19162b
|
fixes, again
|
2024-09-06 11:41:41 -05:00 |
|
|
|
94cf81d38c
|
tweak
|
2024-09-05 23:21:18 -05:00 |
|
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|
413097f5f7
|
fixes
|
2024-09-05 21:42:59 -05:00 |
|
|
|
54547b74d8
|
experimental implementation of STT (need to actually test on a model, test trainer seems to work)
|
2024-09-05 20:43:20 -05:00 |
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|
d319d33368
|
haha
|
2024-09-04 14:52:26 -05:00 |
|
|
|
619369236b
|
ugh
|
2024-08-30 21:10:57 -05:00 |
|
|
|
168e203942
|
ugh
|
2024-08-30 14:39:07 -05:00 |
|
|
|
685f4faec0
|
ugh
|
2024-08-30 10:46:26 -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 |
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|
d423bc03c2
|
fixed attentions for MoE
|
2024-08-27 17:02:42 -05:00 |
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|
b7b99a25f1
|
added ability to specify attention backend for CLI and webui (because im tired of editing the yaml)
|
2024-08-26 19:33:51 -05:00 |
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|
0d706ec6a1
|
added fused_attn (triton-based fused attention) and simply just query for flash_attn under rocm
|
2024-08-26 19:13:34 -05:00 |
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|
|
6b0891448c
|
pain (some shit to try and get some flash attention for ROCm (gfx1100) through triton fused attention but no good)
|
2024-08-25 20:07:27 -05:00 |
|
|
|
40e1799adc
|
fixed xformers and flash_attn to actually work now
|
2024-08-19 01:03:35 -05:00 |
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|
|
29c35528e5
|
the sooner I accept there's no FA for V100s the sooner I'll go to bed
|
2024-08-18 23:54:33 -05:00 |
|
|
|
d636edd3a2
|
added flash_attn LlamaAttention (including flash_attn==1.0.9)
|
2024-08-18 20:51:14 -05:00 |
|
|
|
054d28573a
|
my DAC dataset again managed to only have some utterances with only 8 of 9 RVQ levels, this fixes an oversight from it
|
2024-08-09 21:18:01 -05:00 |
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|
|
2a1794c084
|
ughghghhhh
|
2024-08-09 21:15:01 -05:00 |
|
|
|
ed373957e2
|
maybe not
|
2024-08-09 11:38:08 -05:00 |
|
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|
c658a7b440
|
make loss scaling opt-in rather than automatically determined (because it seems a DAC-based model really doesnt like loss scaling)
|
2024-08-09 10:51:36 -05:00 |
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|
|
d04f6911b4
|
oops
|
2024-08-08 19:38:55 -05:00 |
|
|
|
0aa59e6f3f
|
uncommented block that writes the metadata on HDF5 creation
|
2024-08-08 19:21:29 -05:00 |
|
|
|
79a6781c9e
|
fix vall_e.data --action=hdf5 actually transcribing because past me completely forgot it tried to already put the transcribe/process dataset scripts inside the module before
|
2024-08-08 07:51:42 -05:00 |
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|
949339a3fa
|
do not include SDPA attention if there's no available SDPA backends
|
2024-08-06 20:42:39 -05:00 |
|
|
|
613024ec0d
|
ugh
|
2024-08-06 20:35:15 -05:00 |
|
|
|
eac353cd0b
|
busy work and cleanup while I wait for 1TB of audio to quantize... again.
|
2024-08-06 20:23:33 -05:00 |
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|
f284c7ea9c
|
do mixed-precision for AMP inside the compress function itself, because the loudness function gripes when using a float16 (non-power of 2 lengths) or bfloat16 (something about views for bfloat16)
|
2024-08-06 15:08:37 -05:00 |
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|
|
b6ba2cc8e7
|
tweaked vall_e.emb.process to instead process audio one file at a time instead of all the files for a given speaker to avoid OOMing on less-memory-filled systems with --low-memory
|
2024-08-06 14:24:40 -05:00 |
|
|
|
9710b06b74
|
tweaks and things
|
2024-08-06 08:17:25 -05:00 |
|
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|
134dac8c2b
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re-adapted process_libritts.py to a 'better' way (better because it processed without needing to shuffle a bunch of things and adapt to cope or something)
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2024-08-05 20:34:58 -05:00 |
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3f73fcca29
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oops
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2024-08-05 20:12:13 -05:00 |
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597441e48b
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moved transcribe and process dataset scripts to vall_e/emb within the module itself, argparse-ified transcription script
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2024-08-05 19:40:50 -05:00 |
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7cdfa3dc0c
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updated process_datasets.py, added argparsing so I can mostly stop manually editing things, and some other cleanup
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2024-08-05 15:59:25 -05:00 |
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debcc93e7e
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add adapted MixtralAttention for when I make a bad decision to actually train a MoE
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2024-08-04 22:03:22 -05:00 |
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10aaf840e7
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added export option to convert Llama to MixtralMoE for another dumb experiment
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2024-08-04 20:25:06 -05:00 |
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3a65cc4b22
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fix issue with sft and shared tensors...
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2024-08-04 19:56:21 -05:00 |
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23f3b56fda
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oops
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2024-08-04 08:18:57 -05:00 |
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d19f93a2c0
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documentation update
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2024-08-04 00:14:49 -05:00 |
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2cb465018b
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implicitly load either normal pickled weights or safetensors on loading the model
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2024-08-03 23:34:18 -05:00 |
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c09133d00f
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added safetensors support (with metadata) and feed whatever torch.load/torch.save into it
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2024-08-03 23:15:20 -05:00 |
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6a733eb2ed
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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
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2024-08-03 22:10:21 -05:00 |
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ab673e0426
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add cap for NAR-len training, to avoid any weird cases in early training where it'll just mess up and generate long lengths
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2024-08-03 21:00:32 -05:00 |
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4d2b88b164
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throw exception if training, but no model is set to train (because i ran into this wondering what the hell was happening)
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2024-08-03 20:51:23 -05:00 |
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d0a5c7eca2
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more coping with the NAR len
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2024-08-03 20:23:36 -05:00 |
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11fa3da665
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some cleanup, fixed the wrapper attention to explicitly use other sdpa backends
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2024-08-03 19:51:00 -05:00 |
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