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由于AuraFlow模型比较大，我就下在本地/hf_hub,结果运行Huggingface上README.md的代码
from diffusers import AuraFlowPipeline import torch pipeline = AuraFlowPipeline.from_pretrained( "/hf_hub/fal/AuraFlow-v0.2", torch_dtype=torch.float16, variant="fp16", ).to("cuda") image = pipeline( prompt="close-up portrait of a majestic iguana with vibrant blue-green scales, piercing amber eyes, and orange spiky crest. Intricate textures and details visible on scaly skin. Wrapped in dark hood, giving regal appearance. Dramatic lighting against black background. Hyper-realistic, high-resolution image showcasing the reptile's expressive features and coloration.", height=1024, width=1024, num_inference_steps=50, generator=torch.Generator().manual_seed(666), guidance_scale=3.5, ).images[0] image ValueError: /hf_hub/fal/AuraFlow-v0.2/transformer/ containing more than one
.index.jsonfile, delete the irrelevant ones.
网上并没有资料，我只好做了些尝试，发现是transformer文件夹下index.json重合了。我就用link做了测试
解决方法
删除其中一个index.json。可参考我的目录
fal/ ├── AuraFlow-v0.2 │ ├── aura_flow_0.2.safetensors -> /hf_hub/fal/AuraFlow-v0.2/aura_flow_0.2.safetensors │ ├── model_index.json -> /hf_hub/fal/AuraFlow-v0.2/model_index.json │ ├── scheduler -> /hf_hub/fal/AuraFlow-v0.2/scheduler │ ├── text_encoder -> /hf_hub/fal/AuraFlow-v0.2/text_encoder/ │ ├── tokenizer -> /hf_hub/fal/AuraFlow-v0.2/tokenizer/ │ ├── transformer │ │ ├── config.json -> /hf_hub/fal/AuraFlow-v0.2/transformer/config.json │ │ ├── diffusion_pytorch_model-00001-of-00003.safetensors -> /hf_hub/fal/AuraFlow-v0.2/transformer/diffusion_pytorch_model-00001-of-00003.safetensors │ │ ├── diffusion_pytorch_model-00002-of-00003.safetensors -> /hf_hub/fal/AuraFlow-v0.2/transformer/diffusion_pytorch_model-00002-of-00003.safetensors │ │ ├── diffusion_pytorch_model-00003-of-00003.safetensors -> /hf_hub/fal/AuraFlow-v0.2/transformer/diffusion_pytorch_model-00003-of-00003.safetensors │ │ └── diffusion_pytorch_model.safetensors.index.json -> /hf_hub/fal/AuraFlow-v0.2/transformer/diffusion_pytorch_model.safetensors.index.json │ └── vae -> /hf_hub/fal/AuraFlow-v0.2/vae/ └── AuraFlow-v0.2-fp16 ├── aura_flow_0.2.safetensors -> /hf_hub/fal/AuraFlow-v0.2/aura_flow_0.2.safetensors ├── model_index.json -> /hf_hub/fal/AuraFlow-v0.2/model_index.json ├── scheduler -> /hf_hub/fal/AuraFlow-v0.2/scheduler ├── text_encoder -> /hf_hub/fal/AuraFlow-v0.2/text_encoder/ ├── tokenizer -> /hf_hub/fal/AuraFlow-v0.2/tokenizer/ ├── transformer │ ├── config.json -> /hf_hub/fal/AuraFlow-v0.2/transformer/config.json │ ├── diffusion_pytorch_model-00001-of-00002.fp16.safetensors -> /hf_hub/fal/AuraFlow-v0.2/transformer/diffusion_pytorch_model-00001-of-00002.fp16.safetensors │ ├── diffusion_pytorch_model-00002-of-00002.fp16.safetensors -> /hf_hub/fal/AuraFlow-v0.2/transformer/diffusion_pytorch_model-00002-of-00002.fp16.safetensors │ └── diffusion_pytorch_model.safetensors.fp16.index.json -> /hf_hub/fal/AuraFlow-v0.2/transformer/diffusion_pytorch_model.safetensors.fp16.index.json └── vae -> /hf_hub/fal/AuraFlow-v0.2/vae/ fp16
Fri Aug 2 19:48:23 2024 +-----------------------------------------------------------------------------------------+ | NVIDIA-SMI 555.58.02 Driver Version: 555.58.02 CUDA Version: 12.5 | |-----------------------------------------+------------------------+----------------------+ | GPU Name Persistence-M | Bus-Id Disp.A | Volatile Uncorr. ECC | | Fan Temp Perf Pwr:Usage/Cap | Memory-Usage | GPU-Util Compute M. | | | | MIG M. | |=========================================+========================+======================| | 0 NVIDIA GeForce RTX 4090 Off | 00000000:01:00.0 Off | Off | | 34% 58C P0 407W / 515W | 18542MiB / 24564MiB | 100% Default | | | | N/A | +-----------------------------------------+------------------------+----------------------+ +-----------------------------------------------------------------------------------------+ | Processes: | | GPU GI CI PID Type Process name GPU Memory | | ID ID Usage | |=========================================================================================| | 0 N/A N/A 1124 G /usr/lib/Xorg 167MiB | | 0 N/A N/A 1189 G /usr/bin/sddm-greeter-qt6 146MiB | | 0 N/A N/A 3878 C ...conda3/envs/ai-train/bin/python3.10 18196MiB | +-----------------------------------------------------------------------------------------+ 无fp16
Fri Aug 2 19:50:18 2024 +-----------------------------------------------------------------------------------------+ | NVIDIA-SMI 555.58.02 Driver Version: 555.58.02 CUDA Version: 12.5 | |-----------------------------------------+------------------------+----------------------+ | GPU Name Persistence-M | Bus-Id Disp.A | Volatile Uncorr. ECC | | Fan Temp Perf Pwr:Usage/Cap | Memory-Usage | GPU-Util Compute M. | | | | MIG M. | |=========================================+========================+======================| | 0 NVIDIA GeForce RTX 4090 Off | 00000000:01:00.0 Off | Off | | 36% 44C P0 71W / 515W | 20834MiB / 24564MiB | 0% Default | | | | N/A | +-----------------------------------------+------------------------+----------------------+ +-----------------------------------------------------------------------------------------+ | Processes: | | GPU GI CI PID Type Process name GPU Memory | | ID ID Usage | |=========================================================================================| | 0 N/A N/A 1124 G /usr/lib/Xorg 167MiB | | 0 N/A N/A 1189 G /usr/bin/sddm-greeter-qt6 146MiB | | 0 N/A N/A 4031 C ...conda3/envs/ai-train/bin/python3.10 20488MiB | +-----------------------------------------------------------------------------------------+ 