Create app.py

app.py

@@ -0,0 +1,59 @@
+from transformers import pipeline
+import gradio as gr
+
+# Load distilgpt2 — a small text generation model (82M parameters)
+print("Loading text generation model (distilgpt2)...")
+generator = pipeline(
+    "text-generation",
+    model="distilbert/distilgpt2",
+)
+print("Model loaded!")
+
+
+def generate_text(prompt):
+    """Generate a continuation of the input text."""
+    if not prompt or not prompt.strip():
+        return "Type a sentence or two and watch the model try to continue it."
+
+    # Generate with default settings — no temperature control yet
+    # (that's Session 5!)
+    result = generator(
+        prompt,
+        max_new_tokens=80,
+        num_return_sequences=1,
+        do_sample=True,
+        truncation=True,
+    )
+
+    return result[0]["generated_text"]
+
+
+demo = gr.Interface(
+    fn=generate_text,
+    inputs=gr.Textbox(
+        lines=4,
+        placeholder="Type a sentence or the beginning of a story...",
+        label="Your Prompt",
+    ),
+    outputs=gr.Textbox(
+        label="What the Model Wrote",
+        lines=8,
+    ),
+    title="Text Generator",
+    description=(
+        "This model doesn't classify — it creates. "
+        "Type a sentence and watch it try to write what comes next. "
+        "It's a small model (82M parameters), so the results won't be "
+        "perfect — but it's doing something fundamentally different from "
+        "the classification models we've used so far."
+    ),
+    examples=[
+        ["Monday morning arrived like a gift from the universe — truly, what better way to start the week than"],
+        ["The acceptance letter sat on the kitchen table, and she couldn't stop reading it."],
+        ["The volcano had been dormant for three hundred years. When it finally erupted,"],
+        ["Once upon a time, in a city made entirely of glass,"],
+        ["The capital of France is"],
+    ],
+)
+
+demo.launch()