Update app.py

app.py

@@ -51,7 +51,8 @@ model = torch.hub.load('ultralytics/yolov5', 'custom', path='best.pt', force_rel
 #model = torch.hub.load('path/to/yolov5', 'custom', path='/content/yolov56.pt', source='local')  # local repo
 
 HF_TOKEN = os.getenv("ZIKA_TOKEN_WRITE")
-hf_writer = gr.HuggingFaceDatasetSaver(hf_foken=HF_TOKEN, dataset_name="AllAideas/demo-iazika-flags")
+#hf_writer = gr.HuggingFaceDatasetSaver(hf_foken=HF_TOKEN, dataset_name="AllAideas/demo-iazika-flags")
+hf_writer = gr.HuggingFaceDatasetSaver(hf_foken=HF_TOKEN, dataset_name="AllAideas/demo-iazika-flags", trust_repo=True)
 #hf_writer = gr.HuggingFaceDatasetSaver(HF_TOKEN, "demo-iazika-flags", "AllAideas", False)
 
 def getQuantity(string): 
@@ -147,7 +148,7 @@ iface = gr.Interface(yolo,
 					flagging_options=["Correcto", "Incorrecto", "Casi correcto", "Error", "Otro"],
 					flagging_callback=hf_writer)
 
-iface.launch(enable_queue=True, debug=True)
+iface.launch(ache_examples=True, enable_queue=True, debug=True)
 
 """For YOLOv5 PyTorch Hub inference with **PIL**, **OpenCV**, **Numpy** or **PyTorch** inputs please see the full [YOLOv5 PyTorch Hub Tutorial](https://github.com/ultralytics/yolov5/issues/36).