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4f5c9e518a
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actually use the passed-through sample rate from encode for DAC because it does its own resampling I guess
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2024-04-18 13:32:41 -05:00 |
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545162195b
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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
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2024-04-15 19:54:32 -05:00 |
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9c198eb75a
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added torchscale XMOE integration (because Mixtral 8x7B seems very promising and I want to see if it works)
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2023-12-20 18:45:58 -06:00 |
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0aa2a3cc07
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evaluation/validation passes language ID during training (oops)
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2023-10-29 12:00:40 -05:00 |
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9a6040383e
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make validation samplers ignore sampler type
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2023-10-22 09:01:47 -05:00 |
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3195026dba
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fixed issue with the 'add another target audio to artificially create longer sequences' for HDF5 just duplicating the utterance initially sampled
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2023-10-18 20:38:33 -05:00 |
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09cda7d3f9
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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
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2023-10-16 19:30:38 -05:00 |
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65f500083d
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tweaks to try and get deepspeed quantized inferencing, validating bitsandbytes and deepspeed quantization, nothing seems to work
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2023-10-12 22:21:43 -05:00 |
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8740cdefc6
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added initial support for languages (still testing, marked as model version 3), added experimental 'context extend by limiting the resp context' (untested)
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2023-10-11 20:38:40 -05:00 |
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6045cbce94
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added experimental option to append utterances for training target (emphasis on experimental)
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2023-10-11 17:32:45 -05:00 |
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b4405c98ea
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remove double spaces in the text phonemes (might have caused problems.........)
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2023-10-10 19:18:24 -05:00 |
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87db03dd93
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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)
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2023-10-09 22:03:58 -05:00 |
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893a610fad
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cleanup, use deepspeed inferencing pathway if requested
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2023-10-09 15:24:04 -05:00 |
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27483e56f0
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disabled preparing of SpeechX tasks, added dynamic temperature testing (to-do: test it, credited in the function)
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2023-10-09 13:01:40 -05:00 |
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82f02ae9b1
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oops
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2023-10-06 09:26:52 -05:00 |
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d12877ee09
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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
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2023-10-02 16:52:42 -05:00 |
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a6bfe43590
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added mirostat sampling (given a partially trained model, it got far decent output than I expected, need to test on a better trained model)
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2023-09-18 18:55:41 -05:00 |
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d07c63b9d8
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unified more things with training the AR+NAR monolothic model
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2023-09-12 15:54:41 -05:00 |
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40ef34e1ca
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this embedding class definitely works, and migrating from the previous embedding weights seems to work.
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2023-09-11 14:13:42 -05:00 |
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8a6c203277
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added per-speaker samplers
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2023-09-03 21:27:13 -05:00 |
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922404285c
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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)
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2023-09-02 19:25:43 -05:00 |
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4613781e23
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integrated plot script, added tts-c task token to help the model be able to mix between normal VALL-E and VALL-E continuous
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2023-09-02 16:29:53 -05:00 |
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71e68a8528
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tweaked tts-continuous task
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2023-09-02 13:39:17 -05:00 |
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57db3ccfa8
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shuffled VALL-E continuous as a task tts-c instead, logic fixes for it
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2023-09-02 12:23:40 -05:00 |
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2bc2d08b09
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(need to verify) added modifying model size and config bool to align with VALL-E continuous' methodology
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2023-09-01 17:19:34 -05:00 |
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5c8694db8e
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nasty bandaid if there's no validation dataset specified during training (for example, during finetunes)
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2023-08-30 18:23:05 -05:00 |
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7f4388e591
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added total samples processed and tokens processed (len of text tokens + len of target response tokens)
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2023-08-28 11:02:45 -05:00 |
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87c4bfedba
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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)
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2023-08-27 12:26:12 -05:00 |
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165a1154e0
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Undo naive=False test flag, this shouldn't have made its way in
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2023-08-26 22:00:43 -05:00 |
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78378ed1ce
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overhauled dataloading code to be marginally faster, mostly cleaned up, and can leverage a metadata json to help things out
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2023-08-26 19:53:23 -05:00 |
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0517d620b8
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fixes with the local backend
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2023-08-24 17:05:56 -05:00 |
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22904a8639
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more oversights fixed because I've been using a cached dataloader forever now and didn't catch these problems
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2023-08-24 10:25:33 -05:00 |
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5873c27f1a
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ops
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2023-08-24 09:20:47 -05:00 |
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4585824cd3
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tweaks, including exporting on save/quit
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2023-08-23 16:43:03 -05:00 |
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9c5a33bfd2
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added repo with my weights so far
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2023-08-22 13:09:44 -05:00 |
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7b1b82e0e5
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inferencing cleanup
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2023-08-20 21:36:02 -05:00 |
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a47029065b
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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
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2023-08-20 19:21:54 -05:00 |
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fc576010ce
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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
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2023-08-20 06:29:17 -05:00 |
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2d1a9f10c0
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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)
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2023-08-19 15:06:33 -05:00 |
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f7f6d3bf6d
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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'
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2023-08-19 09:50:07 -05:00 |
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6ca347e1e1
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literally had a urethra moment before going to bed with a way to implement cse/nse tasks
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2023-08-19 01:16:46 -05:00 |
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8f42c578c9
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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
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2023-08-19 00:16:08 -05:00 |
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ae9d38aa31
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forgot to have it pull from specified noise to the hdf5 dataset
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2023-08-18 23:57:07 -05:00 |
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77292c42f9
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tested the training preparation for tasks ns, sr, and tse (I don't expect it to go well with only 2 RVQ bins)
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2023-08-18 23:55:40 -05:00 |
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bbb0563b3d
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pseudocode polyfill stub some other flavor of working on adding the tasks
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2023-08-18 22:22:13 -05:00 |
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2a71486cb6
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preparing for SpeechX extensions
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2023-08-18 20:58:07 -05:00 |
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ced31fd9b7
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removed the sampler as it's very misleading
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2023-08-18 14:47:48 -05:00 |
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8e7f900210
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forgot the =
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2023-08-17 19:07:59 -05:00 |
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3ff7cf8341
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maybe fix evaluation dataset not being capped to cfg.evaluation.size
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2023-08-17 18:56:37 -05:00 |
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ee58db746f
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actually make the evaluation dataset shuffled for sample_type=speaker
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2023-08-17 15:04:45 -05:00 |
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