Update

app.py

@@ -1,16 +1,26 @@
 import gradio as gr
 from transformers import pipeline
 
-generator = pipeline("text2text-generation", model="google/flan-t5-base")  # or flan-t5-large
+# Load the FLAN-T5 Large model
+generator = pipeline("text2text-generation", model="google/flan-t5-large")
 
-
-def generate_text(prompt):
-    # Generate text using FLAN-T5 XXL
-    result = generator(prompt, max_length=200, num_return_sequences=1)
+def generate_text(prompt, max_length=100, temperature=1.0):
+    # Generate text using FLAN-T5 Large
+    result = generator(prompt, max_length=max_length, temperature=temperature, num_return_sequences=1)
     return result[0]["generated_text"]
 
 # Create a Gradio interface
-iface = gr.Interface(fn=generate_text, inputs="text", outputs="text", title="FLAN-T5 XXL Text Generator")
+iface = gr.Interface(
+    fn=generate_text,
+    inputs=[
+        gr.inputs.Textbox(lines=3, placeholder="Enter your prompt here...", label="Prompt"),
+        gr.inputs.Slider(minimum=50, maximum=500, default=100, label="Max Length"),
+        gr.inputs.Slider(minimum=0.1, maximum=1.5, default=1.0, label="Temperature"),
+    ],
+    outputs="text",
+    title="FLAN-T5 Large Text Generator",
+    description="Enter a prompt and generate text using the FLAN-T5 Large model."
+)
 
 # Launch the interface
 iface.launch(share=True)