Which one should I download?
Which one should I download?

[WinError 127] The specified procedure could not be foundWARNING:root:WARNING: [WinError 127] The specified procedure could not be foundNeed to compile C++ extensions to get sparse attention suport. Please run python setup.py build developprepare tokenizerTraceback (most recent call last):
File "/workspace/kohya_ss/train_network.py", line 783, in <module>
train(args)
File "/workspace/kohya_ss/train_network.py", line 146, in train
text_encoder, vae, unet, _ = train_util.load_target_model(args, weight_dtype, accelerator)
File "/workspace/kohya_ss/library/train_util.py", line 3023, in load_target_model
text_encoder, vae, unet, load_stable_diffusion_format = _load_target_model(
File "/workspace/kohya_ss/library/train_util.py", line 2989, in _load_target_modelsubprocess.CalledProcessError: Command '['C:\\Stable-Diffusion\\kohya_ss\\venv\\Scripts\\python.exe', 'train_network.py', '--enable_bucket', '--pretrained_model_name_or_path=runwayml/stable-diffusion-v1-5', '--train_data_dir=C:/Stable-Diffusion/Emma/Process lora/Emma lora/image/', '--resolution=512,512', '--output_dir=C:/Stable-Diffusion/Emma/Process lora/Emma lora/model', '--logging_dir=C:/Stable-Diffusion/Emma/Process lora/Emma lora/log', '--network_alpha=1', '--save_model_as=safetensors', '--network_module=networks.lora', '--text_encoder_lr=5e-5', '--unet_lr=0.0001', '--network_dim=8', '--network_weights=C:/Users/archi/Downloads/LoraLowVRAMSettings.json', '--output_name=last', '--lr_scheduler_num_cycles=1', '--learning_rate=0.0001', '--lr_scheduler=cosine', '--lr_warmup_steps=150', '--train_batch_size=1', '--max_train_steps=1496', '--save_every_n_epochs=1', '--mixed_precision=fp16', '--save_precision=fp16', '--seed=1234', '--cache_latents', '--bucket_reso_steps=64', '--mem_eff_attn', '--gradient_checkpointing', '--xformers', '--use_8bit_adam', '--bucket_no_upscale']' returned non-zero exit status 1.[WinError 127] The specified procedure could not be foundWARNING:root:WARNING: [WinError 127] The specified procedure could not be foundNeed to compile C++ extensions to get sparse attention suport. Please run python setup.py build developprepare tokenizerTraceback (most recent call last):
File "/workspace/kohya_ss/train_network.py", line 783, in <module>
train(args)
File "/workspace/kohya_ss/train_network.py", line 146, in train
text_encoder, vae, unet, _ = train_util.load_target_model(args, weight_dtype, accelerator)
File "/workspace/kohya_ss/library/train_util.py", line 3023, in load_target_model
text_encoder, vae, unet, load_stable_diffusion_format = _load_target_model(
File "/workspace/kohya_ss/library/train_util.py", line 2989, in _load_target_modelsubprocess.CalledProcessError: Command '['C:\\Stable-Diffusion\\kohya_ss\\venv\\Scripts\\python.exe', 'train_network.py', '--enable_bucket', '--pretrained_model_name_or_path=runwayml/stable-diffusion-v1-5', '--train_data_dir=C:/Stable-Diffusion/Emma/Process lora/Emma lora/image/', '--resolution=512,512', '--output_dir=C:/Stable-Diffusion/Emma/Process lora/Emma lora/model', '--logging_dir=C:/Stable-Diffusion/Emma/Process lora/Emma lora/log', '--network_alpha=1', '--save_model_as=safetensors', '--network_module=networks.lora', '--text_encoder_lr=5e-5', '--unet_lr=0.0001', '--network_dim=8', '--network_weights=C:/Users/archi/Downloads/LoraLowVRAMSettings.json', '--output_name=last', '--lr_scheduler_num_cycles=1', '--learning_rate=0.0001', '--lr_scheduler=cosine', '--lr_warmup_steps=150', '--train_batch_size=1', '--max_train_steps=1496', '--save_every_n_epochs=1', '--mixed_precision=fp16', '--save_precision=fp16', '--seed=1234', '--cache_latents', '--bucket_reso_steps=64', '--mem_eff_attn', '--gradient_checkpointing', '--xformers', '--use_8bit_adam', '--bucket_no_upscale']' returned non-zero exit status 1.