Update handler.py

handler.py

@@ -61,7 +61,8 @@ class EndpointHandler():
         self.controlnet = ControlNetModel.from_pretrained(CONTROLNET_MAPPING[self.control_type]["model_id"],torch_dtype=dtype).to(device)
         
         # Load StableDiffusionControlNetPipeline 
-        self.stable_diffusion_id = "runwayml/stable-diffusion-v1-5"
+        self.stable_diffusion_id = "runwayml/v1-5-pruned-emaonly.safetensors
+"
         self.pipe = StableDiffusionControlNetPipeline.from_pretrained(self.stable_diffusion_id, 
                                                                       controlnet=self.controlnet, 
                                                                       torch_dtype=dtype,
@@ -94,11 +95,11 @@ class EndpointHandler():
         # hyperparamters
         negatice_prompt = data.pop("negative_prompt", None)
         num_inference_steps = data.pop("num_inference_steps", 30)
-        guidance_scale = data.pop("guidance_scale", 7.5)
+        guidance_scale = data.pop("guidance_scale", 7.0)
         negative_prompt = data.pop("negative_prompt", None)
         height = data.pop("height", None)
         width = data.pop("width", None)
-        controlnet_conditioning_scale = data.pop("controlnet_conditioning_scale", 0.8)
+        controlnet_conditioning_scale = data.pop("controlnet_conditioning_scale", 0.7)
         
         # process image
         image = self.decode_base64_image(image)