|
|
31f71fa134
|
sampler update (some brainworm just never actually had a sampler for sample_type=path)
|
2024-06-14 16:55:40 -05:00 |
|
|
|
132a02c48b
|
sanity cleanup, backup config yaml for each log file
|
2024-06-09 11:22:52 -05:00 |
|
|
|
4ade2b60ee
|
ugh
|
2024-06-06 21:57:11 -05:00 |
|
|
|
fcac9503e2
|
cleanup
|
2024-06-06 13:08:02 -05:00 |
|
|
|
880b4ecd1b
|
cleanup, putting some thoughts in comments before I forget about them
|
2024-06-05 19:50:06 -05:00 |
|
|
|
3cfc8a96bb
|
oops
|
2024-06-05 10:30:04 -05:00 |
|
|
|
c1fcd889d5
|
reverted automatically disabling split loss calc, since it seems that it's actually cacling loss on prom causes the oddities, maybe
|
2024-06-01 12:34:59 -05:00 |
|
|
|
8cf176ab46
|
ugh
|
2024-06-01 10:46:42 -05:00 |
|
|
|
d0ebce6bac
|
ugh
|
2024-06-01 10:30:13 -05:00 |
|
|
|
39bc019142
|
actually save per-rank sampler states
|
2024-06-01 09:46:32 -05:00 |
|
|
|
85f9684720
|
some cleanup
|
2024-05-25 17:46:52 -05:00 |
|
|
|
3337c69e5a
|
leverage between xformers and torch.backends.cuda.sdp_kernel for attention
|
2024-05-11 17:14:05 -05:00 |
|
|
|
d33c7bb7cf
|
ugh
|
2024-05-11 16:47:19 -05:00 |
|
|
|
0b6499601b
|
sanitizing
|
2024-05-11 16:31:05 -05:00 |
|
|
|
bd0a36ba8d
|
I swear I keep seeing tqdm flicker back a number
|
2024-05-10 18:36:01 -05:00 |
|
|
|
0d5d545a40
|
crammed in DAdaptation (doesn't seem worth it) and ScheduleFree (forgot I wanted to weeks ago, seems promising), optimization wrapper cleanup, test trainer changes, etc.
|
2024-05-09 20:28:20 -05:00 |
|
|
|
277dcec484
|
apparently I got an error for trying to serialize an errant tensor that made its way into the json, this could be remedied easily with recursively traversing the dict and coercing any objects to primitives, but I'm tired and I just want to start training and nap
|
2024-05-04 12:33:43 -05:00 |
|
|
|
c494894261
|
simple DDP wrapper (for my NVlink test)
|
2024-05-04 11:48:26 -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 |
|
|
|
467fa1c5ee
|
wrapper fixes
|
2024-04-16 10:19:02 -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 |
|
|
|
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 |
|
|
|
cce929e136
|
nasty hotfix for transformer's Mixtral throwing an error when batch sizes > 1
|
2024-01-26 19:41:12 -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 |
|
|
|
32d4271ca8
|
fixed issue with training from scratch (oops)
|
2023-10-21 09:55:38 -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 |
|
|
|
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 |
|
|
|
893a610fad
|
cleanup, use deepspeed inferencing pathway if requested
|
2023-10-09 15:24:04 -05:00 |
|
|
|
3db7e7dea1
|
implicitly load checkpoint if deepspeed checkpoint not found, updated setup script to grab the diskcached dataloader things
|
2023-10-06 10:02:45 -05:00 |
|
|
|
4abd6564d1
|
fixed training stats not loading from exported weights, a bit of a readme cleanup, updated example training yaml
|
2023-09-23 19:59:00 -05:00 |
|
|
|
9384900ce6
|
revert the frankensteined "train one model but hotload the other" since it kept loading the last exported weights and I'm not supporting this usecase anymore anyways
|
2023-09-22 13:04:17 -05:00 |
|
|
|
c0b25541e3
|
restructured some things with the model to remove dead weights
|
2023-09-20 19:10:59 -05:00 |
|
|
|
5ac119a6e7
|
added light web UI (need to port the telemetry disabling bandaids from aivc)
|
2023-09-09 16:17:20 -05:00 |
|
|
|
67617d7d69
|
also cull frozen_params in the params optimizer receives to reduce VRAM it consumes
|
2023-09-07 18:27:02 -05:00 |
|
|
|
8837bc34d7
|
added option to specify parameters to freeze per-model in YAML (because I need to see about committing atrocities with convering an AR into an AR+NAR)
|
2023-09-07 18:19:51 -05:00 |
|
|
|
ab5134f385
|
tweaks and fixes
|
2023-09-07 17:08:38 -05:00 |
|
|
|
e7a67410d1
|
oops
|
2023-09-07 09:14:03 -05:00 |
|
|
|
712808494f
|
added support for optional prodigy optimizer (https://github.com/konstmish/prodigy) although it consumes a lot more VRAM per parameter
|
2023-09-06 20:33:16 -05:00 |
|
|
|
100ca6b7d0
|
added option to use SGD optimizer through the YAML, added option to pass in additional optimizer parameters through the YAML, added experimental unified AR+NAR model (does not seem fruitful in testing)
|
2023-09-06 18:58:35 -05:00 |
|
|
|
8a6c203277
|
added per-speaker samplers
|
2023-09-03 21:27:13 -05:00 |
|
|
|
81b05dabb9
|
accurate epoch metric is now reported (based on samples processed / length of dataset's paths, rather than naive assumptions)
|
2023-09-03 08:03:36 -05:00 |
|
|
|
57db3ccfa8
|
shuffled VALL-E continuous as a task tts-c instead, logic fixes for it
|
2023-09-02 12:23:40 -05:00 |
|
|
|
7f4388e591
|
added total samples processed and tokens processed (len of text tokens + len of target response tokens)
|
2023-08-28 11:02:45 -05:00 |
|
|
|
87c4bfedba
|
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)
|
2023-08-27 12:26:12 -05:00 |
|
|
|
0517d620b8
|
fixes with the local backend
|
2023-08-24 17:05:56 -05:00 |
|
