Use existing local model instead of downloading from HuggingFace

model_loader.py

@@ -1,25 +1,15 @@
 # model_loader.py
 import os
-import tempfile
 import tensorflow as tf
-from huggingface_hub import hf_hub_download
 
-# Use temporary directory for model storage
-TEMP_MODEL_DIR = tempfile.mkdtemp(prefix="model_")
-MODEL_PATH = os.path.join(TEMP_MODEL_DIR, "efficientnetv2s.h5")
-REPO_ID = "Miguel764/efficientnetv2s-skin-cancer-classifier"
-FILENAME = "efficientnetv2s.h5"
+# Use the existing local model file
+MODEL_PATH = "model/efficientnetv2s.h5"
 
 def load_model():
     if not os.path.exists(MODEL_PATH):
-        print("Model not found locally. Downloading from Hugging Face...")
-        print(f"Using temporary model directory: {TEMP_MODEL_DIR}")
-        hf_hub_download(
-            repo_id=REPO_ID,
-            filename=FILENAME,
-            local_dir=TEMP_MODEL_DIR
-        )
-    else:
-        print("Model already exists locally.")
-
-    return tf.keras.models.load_model(MODEL_PATH)
+        raise FileNotFoundError(f"Model file not found at {MODEL_PATH}")
+    
+    print(f"Loading model from: {MODEL_PATH}")
+    model = tf.keras.models.load_model(MODEL_PATH)
+    print("Model loaded successfully!")
+    return model

requirements.txt

@@ -3,5 +3,4 @@ uvicorn[standard]
 python-multipart
 numpy
 Pillow
-tensorflow==2.10.0
-huggingface_hub
+tensorflow==2.10.0