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5ba80686e1
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two weeks of agony concludes
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2024-11-18 21:29:28 -06:00 |
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2b29790173
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oops
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2024-11-18 14:12:26 -06:00 |
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6cfdf94bf9
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swap priority to use nar-len if available, added notes
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2024-11-18 09:40:04 -06:00 |
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069b27570f
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set option to set training masking ratio (I don't think for tts a fixed masking ratio is beneficial since the magic of the AR+NAR is being able to still reference the prior sequence of tokens for predicting things)
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2024-11-17 17:04:07 -06:00 |
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23fdba0c98
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tweaks and changes
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2024-11-16 15:49:06 -06:00 |
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39096f8ff3
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redid loss calculation to be cleaner, and position ID generation, and other things (I might need to train the NAR-len from scratch and not resume from an existing checkpoint.........)
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2024-11-14 22:17:47 -06:00 |
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e412e98125
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ugh
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2024-11-14 07:34:22 -06:00 |
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910033343c
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overhauled how the right resp level / classifier gets picked to avoid cringemath
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2024-11-13 13:31:17 -06:00 |
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269648605e
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move NAR-len rvq level 0 to separate embedding
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2024-11-13 11:38:58 -06:00 |
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8286aa54c8
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do not pass timestep token/embedding since it doesn't seem to matter at all after all, fixed training masking rate to 80% because a paper said so
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2024-11-13 09:07:10 -06:00 |
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0f2584eba7
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new meme sampler PogChamp new meme sampler PogChamp (it sort of helps?)
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2024-11-12 22:30:09 -06:00 |
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663f07038d
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haha... (do not create a token dropout/noise mask when not training (this sadly didnt fix NAR-len output))
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2024-11-12 16:41:58 -06:00 |
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b09328069e
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actually do CFG sampling for base AR+NAR tasks
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2024-11-12 13:42:39 -06:00 |
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2495a7ef67
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Fixed STT in the web UI
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2024-11-12 12:49:53 -06:00 |
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8927bad7bc
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actually fixed rep pen (for ar and nar, it seems to help with nar unmasking)
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2024-11-11 21:40:19 -06:00 |
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b1f4db39c8
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threw in CFG sampling for normal model as well to experiment with
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2024-11-11 20:27:38 -06:00 |
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2f56696506
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overhauled inference/sampler kwargs to stop being a bloated mess
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2024-11-11 20:21:16 -06:00 |
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a748e223ce
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tweaks
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2024-11-11 12:40:41 -06:00 |
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48490757da
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fixes
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2024-11-10 20:37:50 -06:00 |
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9def34cd66
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lol
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2024-11-10 12:48:41 -06:00 |
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9cb0b6901b
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unified nar.py into ar_nar.py
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2024-11-10 12:19:48 -06:00 |
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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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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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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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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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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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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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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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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
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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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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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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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75b90be325
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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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04e983b86b
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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
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ugh
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2024-10-12 10:41:35 -05:00 |
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d0ab7d755a
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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
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added experimental entropix sampling support
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2024-10-11 21:18:26 -05:00 |
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75a4c866d6
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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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acdce66d4e
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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
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faster
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2024-10-04 22:30:47 -05:00 |
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a507b769a1
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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
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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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d33a906119
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cleanup for AR_NAR inferencing to allow both TTS and STT tasks simultaneously (need to have training eval do this to though)
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2024-09-06 14:30:12 -05:00 |
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341e19162b
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fixes, again
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2024-09-06 11:41:41 -05:00 |
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94cf81d38c
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tweak
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2024-09-05 23:21:18 -05:00 |
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