app21

app.py

@@ -32,14 +32,17 @@ from langchain_community.document_loaders import WebBaseLoader
 from pydantic import BaseModel
 import shutil
 
+from huggingface_hub import from_pretrained_keras
 
+import tensorflow as tf
+from tensorflow import keras
 
 # Cell 1: Image Classification Model
-image_pipeline = pipeline(task="image-classification", model="microsoft/resnet-50")
+model1 = from_pretrained_keras("rocioadlc/EfficientNetV2L")
 
 def predict_image(input_img):
     predictions = model1.predict(input_img)
-    return input_img, {p["label"]: p["score"] for p in predictions} 
+    return input_img, {p["label"]: p["score"] for p in predictions}
 
 image_gradio_app = gr.Interface(
     fn=predict_image,