Commit Graph

35 Commits

Author SHA1 Message Date
mrq
ec79230965 shuffled web UI options hidden by cfg.experimental to its own tab, expose early exit selection to inferencing (it kinda works naively, still need to implement self-speculation) 2024-11-01 21:30:06 -05:00
mrq
fb8faa295b actually float16(+AMP) and layerskip is bad and will kill the model...... 2024-11-01 18:36:44 -05:00
mrq
9b6c57bc57 third time's the charm (for some reason it escaped me that I should treat early exit loss as an aux_loss to be used with the normal loss, as if I was training a MoE's router) 2024-11-01 12:50:37 -05:00
mrq
76ebef45dc off-by-one... 2024-10-31 13:24:48 -05:00
mrq
b63293cbbe ugh 2024-10-30 22:49:11 -05:00
mrq
a22534e8f4 layer skip training implemented (need to gut the inferencing from the repo, and to actually see if the model can benefit from this) 2024-10-30 20:05:45 -05:00
mrq
fc8dfd8617 made greedy AR sampling viable (and preferable), with caveats (per comment in vall_e.models.ar_nar) 2024-10-18 16:55:00 -05:00
mrq
84005c5b00 entropix apparently processes the entire sequence of logits but it falls apart when doing that 2024-10-13 12:01:12 -05:00
mrq
c800d28bb8 respect attention defined in the yaml for web UI (which might explain why theres been a discrepancy in outputs for me) 2024-10-13 11:02:24 -05:00
mrq
ed6b7a690f ugh......... 2024-10-13 00:26:46 -05:00
mrq
d405f243d4 at wits end in trying to output the right attention scores 2024-10-12 23:53:13 -05:00
mrq
70cf694cfd output attention scores for SDPA/flash, since naive attention seems broken 2024-10-12 12:09:17 -05:00
mrq
04e983b86b modified demo page to be more modular with demoing comparisons, actually provide a path to use modified naive attention, entropix sampling is not tied to an experimental yaml flag now 2024-10-12 11:27:55 -05:00
mrq
3d6ef9666b overridden naive llama attention to get the right score values that entropix needs 2024-10-12 10:05:47 -05:00
mrq
168e203942 ugh 2024-08-30 14:39:07 -05:00
mrq
685f4faec0 ugh 2024-08-30 10:46:26 -05:00
mrq
32287710a2 moved prints to use logger, edited readme (fused_attn doesnt seem stable for training) 2024-08-29 13:27:16 -05:00
mrq
d423bc03c2 fixed attentions for MoE 2024-08-27 17:02:42 -05:00
mrq
0d706ec6a1 added fused_attn (triton-based fused attention) and simply just query for flash_attn under rocm 2024-08-26 19:13:34 -05:00
mrq
6b0891448c pain (some shit to try and get some flash attention for ROCm (gfx1100) through triton fused attention but no good) 2024-08-25 20:07:27 -05:00
mrq
40e1799adc fixed xformers and flash_attn to actually work now 2024-08-19 01:03:35 -05:00
mrq
29c35528e5 the sooner I accept there's no FA for V100s the sooner I'll go to bed 2024-08-18 23:54:33 -05:00
mrq
d636edd3a2 added flash_attn LlamaAttention (including flash_attn==1.0.9) 2024-08-18 20:51:14 -05:00
mrq
2a1794c084 ughghghhhh 2024-08-09 21:15:01 -05:00
mrq
d04f6911b4 oops 2024-08-08 19:38:55 -05:00
mrq
949339a3fa do not include SDPA attention if there's no available SDPA backends 2024-08-06 20:42:39 -05:00
mrq
debcc93e7e add adapted MixtralAttention for when I make a bad decision to actually train a MoE 2024-08-04 22:03:22 -05:00
mrq
10aaf840e7 added export option to convert Llama to MixtralMoE for another dumb experiment 2024-08-04 20:25:06 -05:00
mrq
11fa3da665 some cleanup, fixed the wrapper attention to explicitly use other sdpa backends 2024-08-03 19:51:00 -05:00
mrq
9564ecda43 wrapper attention class for other sdpa backends + xformers seems to have broke... 2024-08-03 15:12:11 -05:00
mrq
ccb14c06ef mamba2-hf using vasqu/mamba2-torch because it lets me use mamba2 without triton ops (training with my 4xV100s are not happy with mamba2 because of triton) 2024-06-14 19:42:17 -05:00
mrq
83eab4fa59 actually going for the suggested "2x layers, no intermediate scaling" is wrong for VALL-E, directly copying the normal transformer structure fixes mamba2 performance in the test trainer 2024-06-13 20:08:22 -05:00
mrq
65a8960305 option to split classifier per-level instead of sharing one (at this point I'm just scrambling to try and cope with training a DAC model, the NAR is being a pain) 2024-06-11 22:28:59 -05:00
mrq
b2194b859a 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) 2024-06-06 09:48:43 -05:00
mrq
ff6fe6f1bc cleanup 2024-06-05 20:30:43 -05:00