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AXERA-TECH / lcm-lora-sdv1-5
Model's Last Updated: May 21 2026
Introduction of lcm-lora-sdv1-5
Model Details of lcm-lora-sdv1-5
SD1.5-LCM.Axera
基于 StableDiffusion 1.5 LCM 项目，展示该项目 文生图 、 图生图 在基于 AX650N 的产品上部署的流程。
支持芯片：
- AX650N
支持硬件
- 爱芯派Pro
- M.2 算力卡
原始模型请参考
模型转换
- 请参考 模型转换文档
运行
-
将编译好的
unet.axmodel,vae_encoder.axmodel,vae_decoder模型拷贝到./models路径下 -
将
Dreamshaper 7仓库中的text_encoder文件夹拷贝到./models路径下 -
在 Huggingface 上的项目已经在
./models存放了 DEMO 展示的必要模型
性能对比
- Raspberry Pi5 使用基于 AX650N 的算力模组拓展，SD1.5 的推理性能可以提升 40 倍！
- 输入图片大小 512x512
| Models | Raspberry Pi5 Only CPU | Raspberry Pi5 + M.2 Card |
|---|---|---|
| UNet(1 step) | 14 s | 0.43 s |
| VAE Encoder | 25 s | 0.46 s |
| VAE Decoder | 58 s | 0.91 s |
| Total txt2img, 4steps | 120 s | 2.68 s |
| Total img2img | 113 s | 2.25 s |
文生图
-
运行
run_txt2img_axe_infer.py
Input Prompt
Self-portrait oil painting, a beautiful cyborg with golden hair, 8k
Output
(sd1_5) axera@raspberrypi:~/samples/sd1.5-lcm.axera $ python run_txt2img_axe_infer.py
[INFO] Available providers: ['AXCLRTExecutionProvider']
prompt: Self-portrait oil painting, a beautiful cyborg with golden hair, 8k
text_tokenizer: ./models/tokenizer
text_encoder: ./models/text_encoder
unet_model: ./models/unet.axmodel
vae_decoder_model: ./models/vae_decoder.axmodel
time_input: ./models/time_input_txt2img.npy
save_dir: ./txt2img_output_axe.png
text encoder take 2891.1ms
[INFO] Using provider: AXCLRTExecutionProvider
[INFO] SOC Name: AX650N
[INFO] VNPU type: VNPUType.DISABLED
[INFO] Compiler version: 3.3 972f38ca
[INFO] Using provider: AXCLRTExecutionProvider
[INFO] SOC Name: AX650N
[INFO] VNPU type: VNPUType.DISABLED
[INFO] Compiler version: 3.3 972f38ca
load models take 26628.9ms
unet once take 437.5ms
unet once take 433.4ms
unet once take 433.6ms
unet once take 433.6ms
unet loop take 1741.2ms
vae inference take 914.8ms
save image take 210.5ms
(sd1_5) axera@raspberrypi:~/samples/sd1.5-lcm.axera $
Output Image
图生图
-
运行
run_txt2img_axe_infer.py
Input Prompt
Astronauts in a jungle, cold color palette, muted colors, detailed, 8k
Input Image
Output
(sd1_5) axera@raspberrypi:~/samples/sd1.5-lcm.axera $ python run_img2img_axe_infer.py
[INFO] Available providers: ['AXCLRTExecutionProvider']
prompt: Astronauts in a jungle, cold color palette, muted colors, detailed, 8k
text_tokenizer: ./models/tokenizer
text_encoder: ./models/text_encoder
unet_model: ./models/unet.axmodel
vae_encoder_model: ./models/vae_encoder.axmodel
vae_decoder_model: ./models/vae_decoder.axmodel
init image: ./models/img2img-init.png
time_input: ./models/time_input_img2img.npy
save_dir: ./img2img_output_axe.png
text encoder take 4494.8ms
[INFO] Using provider: AXCLRTExecutionProvider
[INFO] SOC Name: AX650N
[INFO] VNPU type: VNPUType.DISABLED
[INFO] Compiler version: 3.3-dirty 2ecead35-dirty
[INFO] Using provider: AXCLRTExecutionProvider
[INFO] SOC Name: AX650N
[INFO] VNPU type: VNPUType.DISABLED
[INFO] Compiler version: 3.3 972f38ca
[INFO] Using provider: AXCLRTExecutionProvider
[INFO] SOC Name: AX650N
[INFO] VNPU type: VNPUType.DISABLED
[INFO] Compiler version: 3.3 972f38ca
load models take 27331.3ms
vae encoder inference take 460.4ms
unet once take 433.7ms
unet once take 433.5ms
unet loop take 871.7ms
vae decoder inference take 914.5ms
grid image saved in ./lcm_lora_sdv1-5_imgGrid_output.png
save image take 427.5ms
(sd1_5) axera@raspberrypi:~/samples/sd1.5-lcm.axera $
Output Image
相关项目
NPU 工具链 Pulsar2 在线文档
技术讨论
Github issues QQ 群: 139953715
免责声明
- 本项目只用于指导如何将 Latent Consistency Model (LCM) LoRA: SDv1-5 开源项目的模型部署在基于 AX650N 的相关产品上
- 该模型存在的固有的局限性，可能产生错误的、有害的、冒犯性的或其他不良的输出等内容与 AX650N 以及本仓库所有者无关
- 免责声明
Runs of AXERA-TECH lcm-lora-sdv1-5 on huggingface.co
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More Information About lcm-lora-sdv1-5 huggingface.co Model
Url of lcm-lora-sdv1-5
lcm-lora-sdv1-5 huggingface.co Url
Provider of lcm-lora-sdv1-5 huggingface.co
Other API from AXERA-TECH
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