OutOfMemoryError:CUDA内存不足。尝试分配26.00 MiB(GPU 0; 6.00 GiB总容量; 3.76 GiB已分配; 17.31 MiB可用; PyTorch总共保留了3.96 GiB)如果保留内存>>分配内存,请尝试设置max_split_size_mb以避免碎片。有关内存管理和PYTORCH_CUDA_ALLOC_CONF,请参阅文档时间:15.8秒。 2楼2023-09-24 23:27 回复 古月林...
=== Diagnostic Run torch.onnx.export version 2.0.1+cu118 === verbose: False, log level: Level.ERROR === 0 NONE 0 NOTE 0 WARNING 0 ERROR === ERROR:root:CUDA out of memory. Tried to allocate 50.00 MiB (GPU 0; 23.65 GiB total capacity; 21.71 GiB already allocated; 66.00 MiB free...
目前在开源社区常用的SDXL VAE模型有:sdxl_vae.safetensors、lastpiecexlVAE_baseonA0897.safetensors、fixFP16ErrorsSDXLLowerMemoryUse_v10.safetensors、xlVAEC_f1.safetensors、flatpiecexlVAE_baseonA1579.safetensors等。 这里Rocky使用了6种不同的SDXL VAE模型,在其他参数保持不变的情况下,对比了SDXL...
torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 26.00 MiB (GPU 0; 4.00 GiB total capacity; 2.82 GiB already allocated; 0 bytes free; 2.91 GiB reserved in total by PyTorch) If reserved memory is >> allocated memory try setting max_split_size_mb to avoid fragmentation....
--enable_xformers_memory_efficient_attention \ --checkpointing_steps=5000 \ --validation_steps=5000 \ --report_to wandb \ --push_to_hub 其中主要的参数说明如下: pretrained_model_name_or_path:基础的 Stable Diffusion 模型,这里我们使用 v2-1 版本,因为这一版生成人脸效果更好 ...
vae.set_use_memory_efficient_attention_xformers(True) # Tokenizers tokenizer1 = CLIPTokenizer.from_pretrained(text_encoder_1_name) tokenizer2 = lambda x: open_clip.tokenize(x, context_length=77) # LoRA for weights_file in args.lora_weights: if ";" in weights_file: weights_fil...
# cosumes large memory, so send to GPU before creating the LLLite model accelerator.print("sending U-Net to GPU") unet.to(accelerator.device, dtype=weight_dtype) unet_sd = unet.state_dict() # init LLLite weights accelerator.print(f"initialize U-Net with ControlNet-LLLite") if...
AUTOMATIC1111 is quite different. Again, using an Apple M1, SDXL Turbo takes 6 seconds with 1 step, and Stable Diffusion v1.5 takes 35 seconds with 20 steps. The difference is likely due to the difference in memory management. ComfyUI seems to be offloading the model from memory after ...
- CUDA out of memory: 炸显存 换启动参数 换显卡 - DefaultCPUAllocator: 炸内存 加虚拟内存 加内存条 - CUDA driver initialization failed: 装CUDA驱动 - Training models with lowvram not possible: 这点显存还想炼丹? 部署流程 基础部署流程同云服务器部署步骤一样 注意:显卡配置要求为N卡优先,适配程度高,...
enable_xformers_memory_efficient_attention() source_image = load_image('https://huggingface.co/lllyasviel/control_v11f1e_sd15_tile/resolve/main/images/original.png') condition_image = resize_for_condition_image(source_image, 1024) image = pipe(prompt="best quality", negative_prompt="blur,...