Create app.py

app.py

@@ -0,0 +1,21 @@
+import gradio as gr
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM, pipeline
+
+# Loading summarization model
+summarization_tokenizer = AutoTokenizer.from_pretrained("ieuniversity/sciencebrief_summarization")
+summarization_model = AutoModelForSeq2SeqLM.from_pretrained("ieuniversity/sciencebrief_summarization")
+summarizer = pipeline("summarization", tokenizer=summarization_tokenizer, model=summarization_model)
+
+def summarize(text):
+    return summarizer(text, max_length=120, min_length=30, do_sample=False)[0]['summary_text']
+
+iface_summarize = gr.Interface(
+    fn=summarize,
+    inputs=gr.inputs.Textbox(lines=10, label="Input Text"),
+    outputs=gr.outputs.Textbox(label="Summary"),
+    title="ScienceBrief Summarization",
+    description="Get a summary of your text using the ScienceBrief summarization model.",
+    theme="compact"
+)
+
+iface_summarize.launch()