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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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0427d8d076
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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
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2024-03-01 10:32:35 -06:00 |
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35d78a2bb0
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Yet Another Underlying Transformer Implementation (BitNet, will give it a few days to see how it fares)
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2024-02-29 20:29:17 -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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cce929e136
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nasty hotfix for transformer's Mixtral throwing an error when batch sizes > 1
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2024-01-26 19:41:12 -06:00 |
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e799665759
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experimental weighting of prom/resp embeds
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2024-01-25 12:18:48 -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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e513d2ef19
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experts weren't forwarded into constructer (wasted a few days of training garbage)
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2023-12-23 16:08:17 -06:00 |
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0db3203b21
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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)
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2023-12-22 19:27:36 -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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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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ed54f4ebec
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un 'experimental' the better target sequence preparation
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2023-10-22 09:06:59 -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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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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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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a539f6889f
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mucked around with the loss calculation, this seems better?
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2023-10-13 18:22:21 -05:00 |
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fb467b19ba
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exposed rolling resp context to the web UI, added passing in language to inferencing command line
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2023-10-12 23:21:01 -05:00 |
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298fd9a5f9
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fixed issue with webui
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2023-10-12 22:49:25 -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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08bae355eb
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actually use langs from the dataloader
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2023-10-11 21:21:50 -05:00 |
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3af19d79fd
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oops
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2023-10-11 20:49:54 -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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7facacf7c9
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separated samplers into its own file, don't bother copying the logits back to the GPU after sampling, it's not necessary
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2023-10-11 12:25:31 -05:00 |
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100dd164e6
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apply phoneme cleanup in inferencing as well
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2023-10-10 19:21:19 -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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47b3077415
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fixed mirostat issue
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2023-10-10 18:09:49 -05:00 |
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99e980d323
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documentation and more better-er attribution
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2023-10-10 17:15:16 -05:00 |
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e727b6e5c1
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changed dynamic temperature trigger to be a min-(n)ar-temp value between [0,(n)ar-temp), flags to set min temp, checkbox in web UI to request it
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2023-10-10 17:02:33 -05:00 |
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ec25f56bd9
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used torch.max fixes things, somehow, for dynamic temp sampling
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2023-10-10 16:42:24 -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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26fbb92ec6
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reduced dynamic temperature threshold to > 1.0, as it seems to not quite be useful for audio LMs, sped up any sampling that touches logits by copying them to CPU first, as accessing tensors on the GPU is slow as balls)
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2023-10-09 14:46:17 -05:00 |
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29873e6ded
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extend the max temps in the web UI to actually allow dynamic temp sampling
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2023-10-09 13:30:45 -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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2deb995cc9
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updated setup script
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2023-10-06 20:08:28 -05:00 |
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3db7e7dea1
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implicitly load checkpoint if deepspeed checkpoint not found, updated setup script to grab the diskcached dataloader things
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2023-10-06 10:02:45 -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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63cc9cf37a
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added compat flags for torchscale because the maintainer for torchscale broke compat for existing models
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2023-10-05 16:39:46 -05:00 |
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153f8b293c
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added min-x and min-y arguments to plot.py, helper script to download from my existing checkpoint
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2023-10-04 19:41:37 -05:00 |
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777ba43305
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oops
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2023-10-03 15:01:37 -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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e85b798fbf
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set default NAR levels to max for the web UI
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2023-09-29 19:14:16 -05:00 |
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c7fb740d41
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do not specify a default dtype for the web UI, let it implicitly load from the yaml instead
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2023-09-24 17:54:03 -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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