Add application file

app.py

@@ -0,0 +1,33 @@
+import requests
+
+import gradio as gr
+import torch
+from timm import create_model
+from timm.data import resolve_data_config
+from timm.data.tranforms import create_transform
+
+from transformers import AutoFeatureExtractor, AutoModelForImageClassification
+
+
+extractor = AutoFeatureExtractor.from_pretrained("abhishek/autotrain_fashion_mnist_vit_base")
+model = AutoModelForImageClassification.from_pretrained("abhishek/autotrain_fashion_mnist_vit_base")
+transform = create_transform(
+    **resolve_data_config({}, model=model)
+)
+
+model.eval()
+
+def predict_fn(img):
+    img = img.convert('RGB')
+    img = transform(img).unsqueeze(0)
+
+    with torch.no_grad():
+        out = model(img)
+    
+    probabilites = torch.nn.functional.softmax(out[0], dim=0)
+
+    values, indices = torch.topk(probabilites, k=5)
+
+    return {LABELS[i]: v.item() for i, v in zip(indices, values)}
+
+gr.Interface(predict_fn, gr.inputs.Image(type='pil'), outputs='label').launch()