Update LoRA loading

Dockerfile

@@ -41,4 +41,4 @@ COPY --chown=user . $HOME/app
 ENV LD_PRELOAD=/usr/lib/x86_64-linux-gnu/libtcmalloc.so.4
 # CMD ["uvicorn", "app-img2img:app", "--host", "0.0.0.0", "--port", "7860"]
 # CMD ["uvicorn", "app-txt2img:app", "--host", "0.0.0.0", "--port", "7860"]
-CMD ["uvicorn", "app-controlnet:app", "--host", "0.0.0.0", "--port", "7860"]
+CMD ["uvicorn", "app-controlnetlora:app", "--host", "0.0.0.0", "--port", "7860"]

README.md

@@ -1,5 +1,5 @@
 ---
-title: Real-Time Latent Consistency Model Image-to-Image
+title: Real-Time LCM ControlNet Lora SD1.5
 emoji: 🖼️🖼️
 colorFrom: gray
 colorTo: indigo

app-controlnetlora.py

@@ -77,7 +77,7 @@ controlnet_canny = ControlNetModel.from_pretrained(
 canny_torch = SobelOperator(device=device)
 
 model_id = "nitrosocke/mo-di-diffusion"
-lcm_lora_id = "lcm-sd/lcm-sd1.5-lora"
+lcm_lora_id = "latent-consistency/lcm-lora-sdv1-5"
 
 if SAFETY_CHECKER == "True":
     pipe = StableDiffusionControlNetImg2ImgPipeline.from_pretrained(
@@ -103,8 +103,6 @@ if psutil.virtual_memory().total < 64 * 1024**3:
 # Load LCM LoRA
 pipe.load_lora_weights(
     lcm_lora_id,
-    weight_name="lcm_sd_lora.safetensors",
-    adapter_name="lcm",
     use_auth_token=HF_TOKEN,
 )