Get summarizer to work

app.py

@@ -1,10 +1,15 @@
 import gradio as gr
-from transformers import pipeline
+from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
 
 def summarize(text):
-    summarizer = pipeline("summarization")
-    result = summarizer(text)
-    return result["summary_text"]
+    checkpoint = "sshleifer/distilbart-cnn-12-6"
+    tokenizer = AutoTokenizer.from_pretrained(checkpoint)
+    model = AutoModelForSeq2SeqLM.from_pretrained(checkpoint)
+
+    inputs = tokenizer(text, truncation=True, return_tensors="pt").input_ids
+    outputs = model.generate(inputs, max_new_tokens=100, do_sample=False)
+
+    return tokenizer.decode(outputs[0], skip_special_tokens=True)
 
 iface = gr.Interface(fn=summarize, inputs="text", outputs="text")
 iface.launch()