Update app.py

app.py

@@ -1,12 +1,13 @@
+
 import gradio as gr
-from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+import torch
+import transformers
+from transformers import pipeline
 
-tokenizer = AutoTokenizer.from_pretrained("achimoraites/flan-t5-base-samsum")
-model = AutoModelForSeq2SeqLM.from_pretrained("achimoraites/flan-t5-base-samsum")
+summarizer = pipeline("summarization", model="achimoraites/flan-t5-base-samsum")
 
-def summarize(text,  num_beams=48, max_length=2048):
-    inputs = tokenizer([text], max_length=1024, return_tensors="pt", truncation=True)
-    summary_ids = model.generate(inputs["input_ids"], num_beams=num_beams, min_length=0, max_length=max_length)
-    return tokenizer.batch_decode(summary_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
+def summarize(text):
+    return summarizer(text, max_length=100, min_length=30)[0]['summary_text']
 
-gr.Interface(fn=summarize, inputs="text", outputs="text", live=False).launch()
+iface = gr.Interface(fn=summarize, inputs="text", outputs="text", live=False, capture_session=True)
+iface.launch(inline = False)