mrq 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
..
emb
engines	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
ext	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
models	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
utils	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
__init__.py
__main__.py
config.py	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
data.py	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
export.py
inference.py	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)	2024-01-31 21:48:36 -06:00
plot.py
samplers.py
train.py	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
webui.py	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