Update app.py

app.py

@@ -2,7 +2,7 @@ import streamlit as st
 from transformers import pipeline, GPT2LMHeadModel, AutoTokenizer, BartForConditionalGeneration
 
 generate = pipeline(task='text-generation', model=GPT2LMHeadModel.from_pretrained("DemocracyStudio/generate_nft_content"), tokenizer=AutoTokenizer.from_pretrained("DemocracyStudio/generate_nft_content"))
-summarize=BartForConditionalGeneration.from_pretrained("sshleifer/distilbart-cnn-12-6")
+summarize = pipeline(task='summarization', device=0)
 
 st.title("Text generation for the marketing content of NFTs")
     
@@ -19,10 +19,9 @@ if choice == 'NFT':
         #st.text("Keywords: {}\n".format(keywords))
         #st.text("Length in number of words: {}\n".format(length))
         generated = generate(manual_input, max_length = 512, num_return_sequences=1)
-        st.write(generated[0])
-        for k,v in generated[0].items():
-            tweet = summarize(v)
-            st.write(v)
+        st.write(generated)
+        tweet = summarize(generated[0])
+        st.write(tweet)
 else:
     st.write("Topic not available yet")