chunk_content: name)
  Then, prepare the example for inference.
  
  
  	Copied
  encoding = image_processor(image.convert("RGB"), return_tensors="pt")
  Finally, run inference!
  
  
  	Copied
  with torch.no_grad():
      outputs = inference_model(**encoding)
      logits = outputs.logits
  
  predicted_class_idx = logits.argmax(-1).item()
  print("Predicted class:", inference_model.config.id2label[predicted_class_idx])
  "Predicted class: beignets"
  