Unable to save the unet weights after finetuning the model using text_to_image.py (ValueError: You are trying to save a non contiguous tensor: `conv_in.weight` which is not allowed))
I want to finetune tiny-sd on a different dataset by following text_to_image training (https://huggingface.co/docs/diffusers/main/en/training/text2image) and change the model_name to "segmind/tiny-sd". However, once I run the following code, I get this error.
export MODEL_NAME="segmind/tiny-sd"
export dataset_name="lambdalabs/pokemon-blip-captions"
accelerate launch examples/text_to_image/train_text_to_image.py
--pretrained_model_name_or_path=$MODEL_NAME
--dataset_name=$dataset_name
--use_ema
--resolution=512 --center_crop --random_flip
--train_batch_size=1
--gradient_accumulation_steps=4
--gradient_checkpointing
--mixed_precision="fp16"
--max_train_steps=20
--learning_rate=1e-05
--max_grad_norm=1
--lr_scheduler="constant" --lr_warmup_steps=0
--output_dir="sd-pokemon-model"
======================Error=====================================
Note that the small-sd version doesn't have this problem. Only the tiny-sd version has this issue.
Thank you,
same problem, Only the tiny-sd version has this issue.
segmind/small-sd don't have issue
Same. What the hell bro? :(
Here is a simple reproducible example:
from diffusers import UNet2DConditionModel
unet = UNet2DConditionModel.from_pretrained(
"segmind/tiny-sd", subfolder="unet"
)
unet.save_pretrained("/test")