Add acknowledgement section.

README.md

@@ -34,24 +34,25 @@ from torchvision import transforms
 from models.birefnet import BiRefNet
 
 
+# Load Model
+device = 'cuda'
+torch.set_float32_matmul_precision(['high', 'highest'][0])
+model = BiRefNet.from_pretrained('zhengpeng7/birefnet')
+model.to(device)
+model.eval()
+print('BiRefNet is ready to use.')
+
 # Input Data
 transform_image = transforms.Compose([
     transforms.Resize((1024, 1024)),
     transforms.ToTensor(),
     transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])
 ])
+
 imagepath = 'PATH-TO-YOUR_IMAGE.jpg'
 image = Image.open(imagepath)
 input_images = transform_image(image).unsqueeze(0).to('cuda')
 
-# Load Model
-device = 'cuda'
-torch.set_float32_matmul_precision(['high', 'highest'][0])
-model = BiRefNet.from_pretrained('zhengpeng7/birefnet')
-model.to(device)
-model.eval()
-print('BiRefNet is ready to use.')
-
 # Prediction
 with torch.no_grad():
     preds = model(input_images)[-1].sigmoid().cpu()
@@ -81,6 +82,12 @@ Go to my GitHub page for BiRefNet codes and the latest updates: https://github.c
 + **Online Inference with GUI on Hugging Face** with adjustable resolutions: [![Hugging Face Spaces](https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Spaces-blue)](https://huggingface.co/spaces/ZhengPeng7/BiRefNet_demo)  
 <img src="https://drive.google.com/thumbnail?id=12XmDhKtO1o2fEvBu4OE4ULVB2BK0ecWi&sz=w1080" />
 
+## Acknowledgement:
+
++ Many thanks to @fal for their generous support on GPU resources for training better BiRefNet models.
++ Many thanks to @not-lain for his help on the better deployment of our BiRefNet model on Huggingface.
+
+
 ## Citation
 
 ```