Updated code model loading code completed

app.py

@@ -1,4 +1,64 @@
+import spaces
 import gradio as gr
+import torch
+import numpy as np
+from diffusers import AutoencoderKLWan, WanImageToVideoPipeline
+from diffusers.utils import export_to_video, load_image
+from transformers import CLIPVisionModel
+
+device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+
+## Loading Encoder
+model_id = "Wan-AI/Wan2.1-I2V-14B-480P-Diffusers"
+print(f"Using video Model: {model_id}")
+
+
+print("###### Loading image encoder ######")
+
+image_encoder = CLIPVisionModel.from_pretrained(
+    model_id, subfolder="image_encoder", torch_dtype=torch.float32
+)
+
+
+print("###### Loading VAE encoder ######")
+vae = AutoencoderKLWan.from_pretrained(model_id, subfolder="vae", torch_dtype=torch.float32)
+pipe = WanImageToVideoPipeline.from_pretrained(
+    model_id, vae=vae, image_encoder=image_encoder, torch_dtype=torch.bfloat16
+)
+
+try:
+    pipe.to(device)
+    print(f"Model Loaded in {device}")
+except:
+    print(f"Model loading on {device} failed as trying alternate method")
+try:
+    pipe.to("cuda")
+    print("Model Loaded in cuda")
+except:
+    print(f"Model loading on cuda also failed")
+
+try:
+    pipe.enable_model_cpu_offload()
+    print("Model CPU Offload Completed")
+except:
+    print("Model CPU Offload failed")
+
+
+try:
+    print("Enabling vae Slicing")
+    pipe.enable_vae_slicing()
+    print("VAE Slicing Enabled")
+except:
+    print("Model VAE Slicing Failed")
+
+
+
+
+
+
+
+
+
 
 def greet(name):
     return "Hello " + name + "!!"

requirements.txt

@@ -0,0 +1,5 @@
+diffusers 
+transformers 
+accelerate 
+torch 
+torchvision