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8fffb94964
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backport fix from tortoise_tts with local trainer + loading state when training lora
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2024-06-25 13:41:29 -05:00 |
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8a986eb480
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load exported LoRA weights if exists (to-do: make a better LoRA loading mechanism)
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2024-06-18 21:45:46 -05:00 |
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7cfb78fa64
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enable LoRA for targetted RVQ levels (to experiment with, seems to help)
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2024-06-17 21:45:03 -05:00 |
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7047fcc6e2
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actually make deepspeed work with LoRAs
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2024-06-17 13:55:37 -05:00 |
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1d159b1476
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updated export routine to split LoRA weights from the state dict (should work with deepspeed)
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2024-06-17 13:28:18 -05:00 |
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726a4b613f
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naive, rudimentary DeepSpeed support (just live with the LoRA weights living with the original weights, they can be split later)
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2024-06-17 13:17:24 -05:00 |
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bd0bc10ec0
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added LoRA policy to decide what layer of the model gets adapted based on simple inclusion/exclusion terms
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2024-06-17 13:05:06 -05:00 |
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45a39fb79f
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very rudimentary lora support (no deepspeed support, tested training and saving but not loading yet)
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2024-06-17 00:09:16 -05:00 |
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19410a919e
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ugh
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2024-06-15 12:29:03 -05:00 |
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a7a6e0ac76
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validated that inferencing works, changed some defaults (NAR benefits from greedy sampling)
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2024-06-09 17:11:38 -05:00 |
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132a02c48b
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sanity cleanup, backup config yaml for each log file
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2024-06-09 11:22:52 -05:00 |
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8d92dac829
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forgot I renamed this
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2024-06-09 11:12:30 -05:00 |
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4ade2b60ee
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ugh
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2024-06-06 21:57:11 -05:00 |
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fcac9503e2
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cleanup
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2024-06-06 13:08:02 -05:00 |
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b2194b859a
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re-added loading multiple models because I'm now entertaining having split AR/NAR models again (and need a way to load both at once)
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2024-06-06 09:48:43 -05:00 |
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b05a905b95
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ugh
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2024-06-05 21:02:05 -05:00 |
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e50edc3b48
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added a flag to convert to a HF compatible model on export by stitching things
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2024-06-03 22:34:47 -05:00 |
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934672252b
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feverish cleanup
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2024-06-03 21:28:49 -05:00 |
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c2a436d368
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somehow between training sessions grad_norm = None even though it worked before
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2024-06-02 08:29:27 -05:00 |
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827cf632e7
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report current loss scale and adjust grad norm by loss scale (for deepspeed)
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2024-06-01 10:44:32 -05:00 |
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856545f8bb
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nan loss detection (should have added it earlier), loss scaling for local backend + fp16
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2024-05-11 22:23:29 -05:00 |
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88e9b9caff
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local ddp fix
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2024-05-11 17:29:01 -05:00 |
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71e373064f
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remove redundant loss, tweak readme
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2024-05-11 15:02:47 -05:00 |
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c22a177cf8
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forgot to pass warmup to schedule free
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2024-05-09 22:18:49 -05:00 |
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0d5d545a40
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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.
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2024-05-09 20:28:20 -05:00 |
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8aa1b2dabf
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documentation update
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2024-05-04 21:03:46 -05:00 |
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c494894261
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simple DDP wrapper (for my NVlink test)
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2024-05-04 11:48:26 -05:00 |
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a7b43b98b5
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renamed cfg.bitsandbytes to cfg.optimizations (and having it serve as cfg.optimizations.bitsandbytes)
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2024-05-02 20:08:59 -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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f0c4baeb25
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added Adagrad (experimenting with it), added 'extended' model size (16 layers instead of 12, experimenting with it)
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2024-04-09 22:04:01 -05:00 |
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4d75ee066c
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actually do the Linear replacement with TE's Linear
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2024-04-09 14:41:13 -05:00 |
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9d97eb5104
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added FP8 support through NVIDIA/TransformerEngine, added RetNet_HF through syncdoth/RetNet (as an alternative to branch away from torchscale)
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2024-04-08 20:14:51 -05:00 |
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7075c2a5f0
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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)
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2024-04-04 19:11:49 -05:00 |
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91062361af
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tweaks
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2024-03-01 20:38:06 -06:00 |
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f3c59c3e7e
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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)
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2024-03-01 20:18:43 -06:00 |
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47435207f7
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Added cfg.bitsandbytes.replace as a less intrusive alternative to cfg.bitsandbytes.inject to replace all Linear modules in a model
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2024-03-01 19:20:10 -06:00 |
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3da1518ace
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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)
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2024-01-31 21:48:36 -06:00 |
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c690aa509d
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fixes and compat (MoE-fying an existing model and retraining from there just ruins it after a second of audio...)
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2023-12-25 21:20:32 -06:00 |
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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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6c51a629cc
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resetting step count resets the samples processed and other metrics
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2023-10-29 12:11:19 -05:00 |
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32d4271ca8
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fixed issue with training from scratch (oops)
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2023-10-21 09:55:38 -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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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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4abd6564d1
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fixed training stats not loading from exported weights, a bit of a readme cleanup, updated example training yaml
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2023-09-23 19:59:00 -05:00 |
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e7da1eb90d
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edge case
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2023-09-20 19:20:17 -05:00 |
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c0b25541e3
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restructured some things with the model to remove dead weights
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2023-09-20 19:10:59 -05:00 |
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5ac119a6e7
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added light web UI (need to port the telemetry disabling bandaids from aivc)
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2023-09-09 16:17:20 -05:00 |
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8837bc34d7
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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)
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2023-09-07 18:19:51 -05:00 |
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81b05dabb9
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accurate epoch metric is now reported (based on samples processed / length of dataset's paths, rather than naive assumptions)
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2023-09-03 08:03:36 -05:00 |
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