vall-e/vall_e
2024-07-30 20:53:51 -05:00
..
emb
engines
ext
models added option to set the causal size (how many tokens to sample per AR step), but requires the model to be trained for this (which explains why recurrent chunk sampling just doesn't work for the retnet tests, obvious in hindsight) 2024-07-30 20:53:51 -05:00
utils sanity cleanups with weird off-by-one-ness, cleaned up and validated vall_e.models.experimental works again 2024-07-27 15:36:05 -05:00
__init__.py
__main__.py added option to set the causal size (how many tokens to sample per AR step), but requires the model to be trained for this (which explains why recurrent chunk sampling just doesn't work for the retnet tests, obvious in hindsight) 2024-07-30 20:53:51 -05:00
config.py added option to set the causal size (how many tokens to sample per AR step), but requires the model to be trained for this (which explains why recurrent chunk sampling just doesn't work for the retnet tests, obvious in hindsight) 2024-07-30 20:53:51 -05:00
data.py sanity cleanups with weird off-by-one-ness, cleaned up and validated vall_e.models.experimental works again 2024-07-27 15:36:05 -05:00
demo.py
export.py
inference.py added what I think is DRY sampling 2024-07-29 19:15:07 -05:00
plot.py
samplers.py possible speedup for samplers that require a list of previous tokens (the DRY sampler made me realize that I should copy the tolist() thing from the rep pen sampler for everything else) 2024-07-29 20:23:26 -05:00
train.py sanity cleanups with weird off-by-one-ness, cleaned up and validated vall_e.models.experimental works again 2024-07-27 15:36:05 -05:00
webui.py added option to set the causal size (how many tokens to sample per AR step), but requires the model to be trained for this (which explains why recurrent chunk sampling just doesn't work for the retnet tests, obvious in hindsight) 2024-07-30 20:53:51 -05:00