一,#本机环境检查
执行nvidia-smi,查看右上角。验证显卡驱动已安装最高支持的版本。
nvidia-smi
执行nvcc -V验证cuda
nvcc -V
执行conda --version验证conda版本
conda --version
#列出所有已创建的Conda 环境:
conda env list
或
conda info --envs
#若存在,先删除已存在环境
conda env remove -n diffusers_qwen_image
#创建新环境
conda create -n diffusers_qwen_image python=3.10
#激活环境
conda activate diffusers_qwen_image
二,依赖库安装
#下载diffsynth
git clone https://github.com/modelscope/DiffSynth-Studio.git
#安装diffsynth
cd DiffSynth-Studio
pip install .
#验证diffsynth库是否安装成功
python3 -c "import diffsynth; print('diffsynth导入成功,版本:', diffsynth.__version__)"
#运行文生图
CUDA_VISIBLE_DEVICES=4,5,6,7 python3 -c " from diffsynth.pipelines.qwen_image import QwenImagePipeline, ModelConfig import torchpipe = QwenImagePipeline.from_pretrained(torch_dtype=torch.bfloat16,device='cuda',model_configs=[ModelConfig(model_id='DiffSynth-Studio/Qwen-Image-Distill-Full', origin_file_pattern='diffusion_pytorch_model*.safetensors'),ModelConfig(model_id='Qwen/Qwen-Image', origin_file_pattern='text_encoder/model*.safetensors'),ModelConfig(model_id='Qwen/Qwen-Image', origin_file_pattern='vae/diffusion_pytorch_model.safetensors'),],tokenizer_config=ModelConfig(model_id='Qwen/Qwen-Image', origin_file_pattern='tokenizer/'), ) prompt = '精致肖像,水下少女,蓝裙飘逸,发丝轻扬,光影透澈,气泡环绕,面容恬静,细节精致,梦幻唯美。' image = pipe(prompt, seed=0, num_inference_steps=15, cfg_scale=1) image.save('image.jpg') "