I can only set it in train_network.py. I tried printing args.train_batch_size, it is always 1 no matter how I set it. Here is the command I used: accelerate launch ^ --num_cpu_threads_per_process=2 "D:\KohyaGUI\kohya_ss\sdxl_train_network.py" ^ ...
--train_batch_size=2 \ --max_train_steps=2000 \ --lr_scheduler="cosine" \ --use_8bit_adam 3. 如果還沒下載sd-scripts 如果你還沒下載sd-scripts(kohya-ss),請先執行: git clone https://github.com/kohya-ss/sd-scripts.git cd sd-scripts pip install -r requirements.txt 然後訓練 LoRA ...
D:\train_flux\kohya_ss\venv\lib\site-packages\transformers\tokenization_utils_base.py:1601: FutureWarning:clean_up_tokenization_spaceswas not set. It will be set toTrueby default. This behavior will be depracted in transformers v4.45, and will be then set toFalseby default. For more details...
train_batch_size}") accelerator.print( f" total train batch size (with parallel & distributed & accumulation) / 総バッチサイズ(並列学習、勾配合計含む): {total_batch_size}" ) accelerator.print(f" gradient ccumulation steps / 勾配を合計するステップ数 = {args.gradient_accumulation_...
batch_size=8 # batch size vae_batch_size=4 #vae初始化转换图片批处理大小,2-4。大了可以让一开始处理图片更快 max_train_epoches=20 # max train epoches | 最大训练 epoch save_every_n_epochs=1 # sa2ve every n epochs | 每 N 个 epoch 保存一次 gradient_checkpointing=1 #梯度检查,...
1212 fit_inputs = x + y + sample_weights-> 1213 self._make_train_function() 1214 fit_function = self.train_function 1215 /us 分享回复赞 novelai吧 强攻郭敬明 kohya_ss训练lora时报错,有大佬指点下吗===BUG REPORT=== Welcome to bitsandbytes. For bug reports, please submit your error tra...
File “/content/kohya_ss/library/config_util.py”, line 494, in generate_dataset_group_by_blueprint dataset.make_buckets() File “/content/kohya_ss/library/train_util.py”, line 738, in make_buckets info.image_size = self.get_image_size(info.absolute_path) ...
prior_loss_weight=1.0 --resolution=448,640 --train_batch_size=1 --learning_rate=1e-4 --max_train_steps=400 --use_8bit_adam --xformers --mixed_precision=fp16 --save_every_n_epochs=1 --save_model_as=safetensors --clip_skip=2 --seed=42 --color_aug --network_module=networks....
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batch_size=args.get("batch_size"), image_dir=train_images_dir, conditioning_data_dir=conditioning_images_dir, caption_extension=caption_extension, num_repeats=args.get("num_repeats"), ) return ( train_images_dir, ) def MZ_KohyaSSUseConfig_call(args={}): args = args.copy...