Update app.py

app.py

@@ -1,6 +1,6 @@
-# import gradio as gr
+import gradio as gr
 
-# gr.load("models/microsoft/Phi-3.5-mini-instruct",  max_batch_size=1000).launch(share=True)
+gr.load("models/microsoft/Phi-3.5-mini-instruct",  max_batch_size=1000).launch(share=True)
 
 
 
@@ -112,26 +112,26 @@
 
 
 
-import gradio as gr
-from transformers import pipeline
-huggingface-cli login
+# import gradio as gr
+# from transformers import pipeline
+# huggingface-cli login
 
-text_generator = pipeline("text-generation", model="meta-llama/Llama-3.2-1B")
+# text_generator = pipeline("text-generation", model="meta-llama/Llama-3.2-1B")
 
-def predict(input_text):
-    predictions = text_generator(input_text, max_new_tokens=50, num_return_sequences=1)
-    return predictions[0]["generated_text"]
+# def predict(input_text):
+#     predictions = text_generator(input_text, max_new_tokens=50, num_return_sequences=1)
+#     return predictions[0]["generated_text"]
 
-gradio_app = gr.Interface(
-    predict,
-    inputs=gr.Textbox(label="Enter text for generation"),
-    outputs=gr.Textbox(label="Generated Text"),
-    title="Text Generation Model",
-    description="This app generates text based on input prompts."
-)
+# gradio_app = gr.Interface(
+#     predict,
+#     inputs=gr.Textbox(label="Enter text for generation"),
+#     outputs=gr.Textbox(label="Generated Text"),
+#     title="Text Generation Model",
+#     description="This app generates text based on input prompts."
+# )
 
-if __name__ == "__main__":
-    gradio_app.launch()
+# if __name__ == "__main__":
+#     gradio_app.launch()