add readme

readme.md

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+# Wan2.1 I2V model (480p)
+
+example
+
+```python
+from diffusers.utils import load_image, export_to_video
+from transformers import CLIPVisionModel, CLIPImageProcessor, UMT5EncoderModel, AutoTokenizer
+from diffusers import WanI2VPipeline, WanTransformer3DModel, UniPCMultistepScheduler, AutoencoderKLWan
+import torch
+
+tokenizer = AutoTokenizer.from_pretrained("google/umt5-xxl")
+text_encoder = UMT5EncoderModel.from_pretrained("google/umt5-xxl", torch_dtype=torch.bfloat16)
+vae = AutoencoderKLWan.from_pretrained("StevenZhang/Wan2.1-VAE_Diff")
+
+
+pipe = WanI2VPipeline.from_pretrained(
+    'ypyp/wan2.1_i2v_480p',
+    tokenizer=tokenizer,
+    text_encoder=text_encoder,
+    vae=vae,
+)
+
+image = load_image(
+    "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/astronaut.jpg"
+)
+device = "cuda"
+seed = 0
+prompt = ("An astronaut hatching from an egg, on the surface of the moon, the darkness and depth of space realised in "
+          "the background. High quality, ultrarealistic detail and breath-taking movie-like camera shot.")
+generator = torch.Generator(device=device).manual_seed(seed)
+
+pipe.to(device)
+pipe.enable_model_cpu_offload()
+
+inputs = {
+    'image': image,
+    "prompt": prompt,
+    'max_area': 480 * 832,
+    "generator": generator,
+    "num_inference_steps": 50,
+    "guidance_scale": 5.0,
+    "num_frames": 81,
+    "max_sequence_length": 512,
+    "output_type": "np",
+    'flow_shift': 3.0
+}
+
+output = pipe(**inputs).frames[0]
+export_to_video(output, "output.mp4", fps=15)
+
+```