Create app.py

app.py

@@ -0,0 +1,26 @@
+import gradio as gr
+from transformers import pipeline
+
+def summarize_article(article, model_name, max_length, temperature, top_k, top_p):
+    summarizer = pipeline("summarization", model=model_name)
+    top_k = int(round(top_k))
+    max_length = int(round(max_length))
+    summary = summarizer(article, max_length=max_length, min_length=30, do_sample=True, temperature=temperature, top_k=top_k, top_p=top_p)
+    return summary[0]['summary_text']
+
+iface = gr.Interface(
+    fn=summarize_article,
+    inputs=[
+        "text", 
+        gr.inputs.Dropdown(["Falconsai/text_summarization", "Other Models..."], label="Select Model"),
+        gr.inputs.Number(default=100, label="Max-Length"),
+        gr.inputs.Slider(minimum=0.1, maximum=1.999, default=0.7, label="Temperature"), 
+        gr.inputs.Number(default=50, label="Top-k"),
+        gr.inputs.Number(default=0.9, label="Top-p")
+    ],
+    outputs="text",
+    title="Text Summarization with Hyperparameters",
+    description="Enter an article, select a model, and adjust hyperparameters for summarization."
+)
+
+iface.launch(debug=True)