Update README.md

README.md

@@ -6,3 +6,64 @@ library_name: timm
 license: apache-2.0
 ---
 # Model card for kat_tiny_patch16_224.vitft
+
+---
+tags:
+- image-classification
+- timm
+library_name: timm
+license: apache-2.0
+---
+
+KAT model trained on ImageNet-1k (1 million images, 1,000 classes) at resolution 224x224. It was first introduced in the paper Kolmogorov–Arnold Transformer.
+
+## Model description
+KAT is a model that replaces channel mixer in transfomrers with Group Rational Kolmogorov–Arnold Network (GR-KAN).
+
+## Usage
+The model definition is at https://github.com/Adamdad/kat, `katransformer.py`. 
+
+```python
+from urllib.request import urlopen
+from PIL import Image
+import timm
+import torch
+import katransformer
+
+img = Image.open(urlopen(
+    'https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/beignets-task-guide.png'
+))
+
+# Move model to CUDA
+device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
+
+model = timm.create_model("hf_hub:adamdad/kat_tiny_patch16_224.vitft", pretrained=True)
+model = model.to(device)
+model = model.eval()
+
+
+
+# get model specific transforms (normalization, resize)
+data_config = timm.data.resolve_model_data_config(model)
+transforms = timm.data.create_transform(**data_config, is_training=False)
+
+output = model(transforms(img).unsqueeze(0).to(device))  # unsqueeze single image into batch of 1
+
+top5_probabilities, top5_class_indices = torch.topk(output.softmax(dim=1) * 100, k=5)
+print(top5_probabilities)
+print(top5_class_indices)
+
+```
+
+## Bibtex
+```bibtex
+@misc{yang2024compositional,
+    title={Kolmogorov–Arnold Transformer},
+    author={Xingyi Yang and Xinchao Wang},
+    year={2024},
+    eprint={XXXX},
+    archivePrefix={arXiv},
+    primaryClass={cs.CV}
+}
+```
+