From b8896aad400222c8c4441b217fda0f9bb0807ffd Mon Sep 17 00:00:00 2001 From: Kohya S Date: Thu, 11 Jul 2024 08:01:23 +0900 Subject: [PATCH] update README --- README.md | 6 ++++-- 1 file changed, 4 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index 3eed636c..5d4f9621 100644 --- a/README.md +++ b/README.md @@ -4,7 +4,9 @@ This repository contains training, generation and utility scripts for Stable Dif SD3 training is done with `sd3_train.py`. -__Jun 29, 2024__: Fixed mixed precision training with fp16 is not working. Fixed the model is in bf16 dtype even without `--full_bf16` option (this could worsen the training result). +__Jul 11, 2024__: Fixed to work t5xxl with `fp16`. If you change the dtype to `fp16` for t5xxl, please remove existing latents cache files (`*_sd3.npz`). The shift in `sd3_minimum_inference.py` is fixed to 3.0. Thanks to araleza! + +Jun 29, 2024: Fixed mixed precision training with fp16 is not working. Fixed the model is in bf16 dtype even without `--full_bf16` option (this could worsen the training result). `fp16` and `bf16` are available for mixed precision training. We are not sure which is better. @@ -12,7 +14,7 @@ __Jun 29, 2024__: Fixed mixed precision training with fp16 is not working. Fixed `clip_l`, `clip_g` and `t5xxl` can be specified if the checkpoint does not include them. -t5xxl doesn't seem to work with `fp16`, so 1) use`bf16` for mixed precision, or 2) use `bf16` or `float32` for `t5xxl_dtype`. +~~t5xxl doesn't seem to work with `fp16`, so 1) use`bf16` for mixed precision, or 2) use `bf16` or `float32` for `t5xxl_dtype`. ~~ t5xxl works with `fp16` now. There are `t5xxl_device` and `t5xxl_dtype` options for `t5xxl` device and dtype.