melakukan load langsung di repo model app.py dan menambahkan YAML di README.md

README.md

@@ -1,3 +1,30 @@
+---
+title: HistoryLens
+emoji: 👍
+colorFrom: purple
+colorTo: red
+sdk: gradio
+sdk_version: 5.33.0
+app_file: app.py
+pinned: false
+license: apache-2.0
+short_description: Classification Image using MobileNetV2
+metrics:
+  - accuracy
+pipeline_tag: image-classification
+library_name: keras
+tags:
+  - capstone
+  - image-classification
+  - keras
+  - computer-vision
+  - gradio
+  - historycal-sites
+  - tensorflow
+datasets:
+  - custom
+---
+
 # HistoryLens - Capstone DBS Coding Camp
 
 Proyek ini adalah aplikasi klasifikasi gambar berbasis deep learning untuk mengenali situs cagar budaya di Daerah Istimewa Yogyakarta (DIY). Dibuat menggunakan Gradio dan TensorFlow/Keras, ditujukan untuk membantu pengguna mengenali tempat bersejarah hanya dengan mengunggah foto.

app.py

@@ -13,6 +13,8 @@ from tensorflow.keras.preprocessing import image
 from tensorflow.keras.models import model_from_json
 from PIL import Image
 
+from huggingface_hub import hf_hub_download
+
 from description import description
 from location import location
 
@@ -23,7 +25,11 @@ def load_model_from_file(json_path, h5_path):
     model.load_weights(h5_path)
     return model
 
-model = load_model_from_file("model.json", "my_model.h5")
+# Load model langsung dari Hugging Face Hub
+model_json_path = hf_hub_download(repo_id="CapstoneML/Model", filename="model.json")
+model_weights_path = hf_hub_download(repo_id="CapstoneML/Model", filename="my_model.h5")
+
+model = load_model_from_file(model_json_path, model_weights_path)
 
 labels = [
     "Benteng Vredeburg", "Candi Borobudur", "Candi Prambanan", "Gedung Agung Istana Kepresidenan",