Added LatentConsistencyModel Pipeline functionality

model_loading.py

@@ -7,7 +7,8 @@ if torch.cuda.is_available():
 else:
     device = 'cpu'
     
-validT2IModelTypes = ["KandinskyPipeline", "StableDiffusionPipeline", "DiffusionPipeline", "StableDiffusionXLPipeline"]
+validT2IModelTypes = ["KandinskyPipeline", "StableDiffusionPipeline", "DiffusionPipeline", "StableDiffusionXLPipeline",
+                      "LatentConsistencyModelPipeline"]
 def check_if_model_exists(repoName):
     modelLoaded = None
     huggingFaceURL = "https://huggingface.co/" + repoName + "/raw/main/model_index.json"
@@ -44,8 +45,11 @@ def import_model(modelID, modelType):
         if modelType == 'StableDiffusionXLPipeline':
             from diffusers import StableDiffusionXLPipeline
             T2IModel = StableDiffusionXLPipeline.from_pretrained(modelID, torch_dtype=torch.float16)
+        elif modelType == 'LatentConsistencyModelPipeline':
+            from diffusers import DiffusionPipeline
+            T2IModel = DiffusionPipeline.from_pretrained(modelID, torch_dtype=torch.float16)
         else:
             from diffusers import AutoPipelineForText2Image
             T2IModel = AutoPipelineForText2Image.from_pretrained(modelID, torch_dtype=torch.float16)
-        T2IModel.to(device)
+        T2IModel.to("cuda")
     return T2IModel