initial commit with gradio

app.py

@@ -1,7 +1,22 @@
 import gradio as gr
+from transformers import BartForConditionalGeneration
+from transformers import BartTokenizer
 
-def greet(name):
-    return "Hello " + name + "!!"
+tokenizer = BartTokenizer.from_pretrained('facebook/bart-large-cnn')
+model = BartForConditionalGeneration.from_pretrained('facebook/bart-large-cnn')
 
-demo = gr.Interface(fn=greet, inputs="text", outputs="text")
+
+def generate_summary(text, model, tokenizer):
+    inputs = tokenizer.encode("summarize: " + text, return_tensors="pt", max_length=1024, truncation=True)
+    summary_ids = model.generate(inputs, max_length=150, min_length=50, length_penalty=2.0, num_beams=4, early_stopping=True)
+    summary = tokenizer.decode(summary_ids[0], skip_special_tokens=True)
+    return summary
+
+
+def process(text):
+    return generate_summary(text, model, tokenizer)
+
+
+textbox = gr.Textbox(label="Pega el text aca:", placeholder="Texto...", lines=15)
+demo = gr.Interface(fn=process, inputs=textbox, outputs="text")
 demo.launch()