Update app.py

app.py

@@ -32,7 +32,7 @@ m = torch.load('model.pt', map_location=torch.device('cpu'))
 model.load_state_dict(m)
 model.to(device);
 
-str = st.text_input( 'Enter 1-4 words of the beginning of the text, and wait a minute' , 'The man asks the waiter' )
+str = st.text_input( 'Enter 1-4 words of the beginning of the text, and wait a minute' , '' )
 
 # model without additional training
 # prompt is a string that will be accepted as input and continued by the model
@@ -59,7 +59,7 @@ out1 = model_init.generate(
     # how much (try) not to repeat n_gram in a row
     no_repeat_ngram_size=3,
     # how many generations to return
-    num_return_sequences=3,
+    num_return_sequences=1,
     ).cpu().numpy() #).numpy()
 
 st.write('\n------------------\n')
@@ -88,12 +88,4 @@ with torch.inference_mode():
         top_p=0.6,
         no_repeat_ngram_size=2,
         num_return_sequences=3,
-        ).cpu().numpy() #).cpu().numpy()
-    
-    st.subheader( 'Texts on a model trained with documents of all subjects and retrained with jokes:' )
-    n = 0
-    for out_ in out2:
-        n += 1
-        st.write(tokenizer.decode(out_).rpartition('.')[0],'.')
-        # print(textwrap.fill(tokenizer.decode(out_), 100), end='\n------------------\n')
-        st.write('\n------------------\n')
+        ).cpu().numpy() #).cpu().numpy()