update readme

README.md

@@ -1,3 +1,54 @@
 ---
 license: mit
----
+--- 
+# Unique3d-Normal-Diffuser Model Card 
+
+## Example  
+Note the input image is suppose to be **white background**. 
+```bash 
+import torch 
+import numpy as np 
+from PIL import Image 
+from pipeline import StableDiffusionImage2MVCustomPipeline
+from diffusers import EulerAncestralDiscreteScheduler
+
+# opts 
+seed = -1    
+generator = torch.Generator(device='cuda').manual_seed(-1)
+forward_args = dict(
+    width=512,
+    height=512, 
+    width_cond=512,
+    height_cond=512, 
+    generator=generator,
+    guidance_scale=1.5,   
+    num_inference_steps=30, 
+    num_images_per_prompt=1, 
+)  
+
+# load 
+pipe = StableDiffusionImage2MVCustomPipeline.from_pretrained( 
+    "Luffuly/unique3d-normal-diffuser", 
+    torch_dtype=torch.bfloat16, 
+    trust_remote_code=True,  
+).to("cuda")  
+
+# load image 
+image = Image.open('image.png').convert("RGB") 
+
+# forward 
+out = pipe(image, **forward_args).images 
+out[0].save(f"out.png")
+```
+
+## Citation
+```bash 
+@misc{wu2024unique3d,
+      title={Unique3D: High-Quality and Efficient 3D Mesh Generation from a Single Image}, 
+      author={Kailu Wu and Fangfu Liu and Zhihan Cai and Runjie Yan and Hanyang Wang and Yating Hu and Yueqi Duan and Kaisheng Ma},
+      year={2024},
+      eprint={2405.20343},
+      archivePrefix={arXiv},
+      primaryClass={cs.CV}
+}
+```