|
|
c494894261
|
simple DDP wrapper (for my NVlink test)
|
2024-05-04 11:48:26 -05:00 |
|
|
|
783db3d2c5
|
forgot to commit the DAC test utterance
|
2024-05-04 09:46:51 -05:00 |
|
|
|
a7b43b98b5
|
renamed cfg.bitsandbytes to cfg.optimizations (and having it serve as cfg.optimizations.bitsandbytes)
|
2024-05-02 20:08:59 -05:00 |
|
|
|
b5d1456a09
|
backwards compat for my shitty old weights (was testing if disabling AudioEmbedding summing magically made things better (it did not))
|
2024-04-29 22:14:01 -05:00 |
|
|
|
5120ffdda7
|
god it would be nice to know the best way to handle audio embeddings, because I genuinely don't know without skimming through papers or devoting X amount of GPU hours in training
|
2024-04-29 18:24:05 -05:00 |
|
|
|
6a11bc9cb6
|
update tokenizer because, for some reason, it had the wrong order for the special tokens to where eos = unk
|
2024-04-29 09:09:26 -05:00 |
|
|
|
57810e4ba4
|
metadata only path (might drop HDF5 since its giving file sizes twice as large as my actual unpacked dataset)
|
2024-04-28 23:03:09 -05:00 |
|
|
|
caad7ee3c9
|
final tweaks, hopefully
|
2024-04-28 22:28:29 -05:00 |
|
|
|
ffc334cf58
|
added dataset transcription helper script (now I don't ever have to touch ai-voice-cloning) (to-do: unify scripts into the module)
|
2024-04-21 17:43:20 -05:00 |
|
|
|
b251669536
|
forgot to fix up the test trainer
|
2024-04-21 14:58:04 -05:00 |
|
|
|
071fb97777
|
dataset preparation script updates, caved and am using HF tokenizer now
|
2024-04-21 14:49:18 -05:00 |
|
|
|
a8ffa88844
|
it slipped my mind that technically DAC can be used at any sample rate, since it models waveforms; make it a config YAML option to allow this behavior
|
2024-04-19 18:36:54 -05:00 |
|
|
|
00804a47e9
|
Forgot to copy intermediary dataset conversion script
|
2024-04-18 21:34:28 -05:00 |
|
|
|
8214aa23d7
|
converting over to a different intermediary dataset format
|
2024-04-18 21:24:06 -05:00 |
|
|
|
4f5c9e518a
|
actually use the passed-through sample rate from encode for DAC because it does its own resampling I guess
|
2024-04-18 13:32:41 -05:00 |
|
|
|
2e9e6e68f7
|
Forgot I need to use the DAC's 44K model because 24K model has 32 codebooks instead of 9.
|
2024-04-17 20:59:25 -05:00 |
|
|
|
5ff2b4aab5
|
finally swallowing the Descript-Audio-Codec pill (I guess I'm going to have to regenerate my entire dataset)
|
2024-04-17 20:39:35 -05:00 |
|
|
|
b0bd88833c
|
refractor cleanup, had a revelation on how I can handle a batch of varying tasks
|
2024-04-16 21:04:48 -05:00 |
|
|
|
467fa1c5ee
|
wrapper fixes
|
2024-04-16 10:19:02 -05:00 |
|
|
|
aa1e25fbf5
|
backwards compat for old YAMLs with models, option to set flash attention 2 for Llama (and derivatives), included syncdoth/RetNets torchscale retnet for shits and grins, etc.
|
2024-04-16 10:02:31 -05:00 |
|
|
|
545162195b
|
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
|
2024-04-15 19:54:32 -05:00 |
|
|
|
d69a00e389
|
Properly pass retention_mask for retnet-HF, attempt to fix recurrent forward for retnet (doesn't work still)
|
2024-04-14 13:12:50 -05:00 |
|
|
|
789bb5d11b
|
add an optional label override for model loading (used for easy testing between 12/16/20/24 layered model)
|
2024-04-13 12:43:35 -05:00 |
|
|
|
f0c4baeb25
|
added Adagrad (experimenting with it), added 'extended' model size (16 layers instead of 12, experimenting with it)
|
2024-04-09 22:04:01 -05:00 |
|
|
|
4d75ee066c
|
actually do the Linear replacement with TE's Linear
|
2024-04-09 14:41:13 -05:00 |
|
|
|
9d97eb5104
|
added FP8 support through NVIDIA/TransformerEngine, added RetNet_HF through syncdoth/RetNet (as an alternative to branch away from torchscale)
|
2024-04-08 20:14:51 -05:00 |
|
|
|
7075c2a5f0
|
added an option to allow injecting embeddings from another model, because it dawned upon me how valuable embeddings from a good model can be for subsequent trainings (defined under cfg.models._embeddings as a relative path to the yaml)
|
2024-04-04 19:11:49 -05:00 |
|
|
|
91062361af
|
tweaks
|
2024-03-01 20:38:06 -06:00 |
|
|
|
f3c59c3e7e
|
cleaner replacement code (because I realized BitNet had an implementation for it too), added calculating gradient norm and performing gradient clipping in local trainer (non-deepspeed)
|
2024-03-01 20:18:43 -06:00 |
|
|
|
47435207f7
|
Added cfg.bitsandbytes.replace as a less intrusive alternative to cfg.bitsandbytes.inject to replace all Linear modules in a model
|
2024-03-01 19:20:10 -06:00 |
|
|
|
0427d8d076
|
logger broke for some reason, added flag to just tqdm.write instead, make cfg.bitsandbytes.bitnet==True yamls denoted since I'm sure they're not interoperable
|
2024-03-01 10:32:35 -06:00 |
|
|
|
35d78a2bb0
|
Yet Another Underlying Transformer Implementation (BitNet, will give it a few days to see how it fares)
|
2024-02-29 20:29:17 -06:00 |
|
|
|
3da1518ace
|
added Mistral (non-Mixtral) backend, useless optimization when not training, proper adjustment of the LR for Prodigyopt through d_coeff (maybe), recurrent sampling for LLaMA/Mistral/Mixtral backends (again, doesn't actually work)
|
2024-01-31 21:48:36 -06:00 |
|
|
|
cce929e136
|
nasty hotfix for transformer's Mixtral throwing an error when batch sizes > 1
|
2024-01-26 19:41:12 -06:00 |
|
|
|
e799665759
|
experimental weighting of prom/resp embeds
|
2024-01-25 12:18:48 -06:00 |
|
|
|
c690aa509d
|
fixes and compat (MoE-fying an existing model and retraining from there just ruins it after a second of audio...)
|
2023-12-25 21:20:32 -06:00 |
|
|
|
e513d2ef19
|
experts weren't forwarded into constructer (wasted a few days of training garbage)
|
2023-12-23 16:08:17 -06:00 |
|
|
|
0db3203b21
|
added LLaMA/Mixtral (if experts>1) model arches, utilize XMoE's loss as well, set MoE frequency to 1 to make every layer MoE'd for RetNet, etc. (going to do tests without burning out again to see how things go)
|
2023-12-22 19:27:36 -06:00 |
|
|
|
9c198eb75a
|
added torchscale XMOE integration (because Mixtral 8x7B seems very promising and I want to see if it works)
|
2023-12-20 18:45:58 -06:00 |
|
|
|
6c51a629cc
|
resetting step count resets the samples processed and other metrics
|
2023-10-29 12:11:19 -05:00 |
|
|
|
0aa2a3cc07
|
evaluation/validation passes language ID during training (oops)
|
2023-10-29 12:00:40 -05:00 |
|
|
|
ed54f4ebec
|
un 'experimental' the better target sequence preparation
|
2023-10-22 09:06:59 -05:00 |
|
|
|
9a6040383e
|
make validation samplers ignore sampler type
|
2023-10-22 09:01:47 -05:00 |
|
|
|
32d4271ca8
|
fixed issue with training from scratch (oops)
|
2023-10-21 09:55:38 -05:00 |
|
|
|
3195026dba
|
fixed issue with the 'add another target audio to artificially create longer sequences' for HDF5 just duplicating the utterance initially sampled
|
2023-10-18 20:38:33 -05:00 |
|
|
|
09cda7d3f9
|
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
|
2023-10-16 19:30:38 -05:00 |
|
|
|
a539f6889f
|
mucked around with the loss calculation, this seems better?
|
2023-10-13 18:22:21 -05:00 |
|
|
|
fb467b19ba
|
exposed rolling resp context to the web UI, added passing in language to inferencing command line
|
2023-10-12 23:21:01 -05:00 |
|
|
|
298fd9a5f9
|
fixed issue with webui
|
2023-10-12 22:49:25 -05:00 |
|
|
|
65f500083d
|
tweaks to try and get deepspeed quantized inferencing, validating bitsandbytes and deepspeed quantization, nothing seems to work
|
2023-10-12 22:21:43 -05:00 |
|
