Update app.py

app.py

@@ -2,17 +2,26 @@ import streamlit as st
 import transformers
 
 
-model = transformers.AutoModelForCausalLM.from_pretrained("distilgpt2")
-tokenizer = transformers.AutoTokenizer.from_pretrained("distilgpt2")
+@st.cache
+def load_stuff():
+    model = transformers.AutoModelForCausalLM.from_pretrained("distilgpt2")
+    tokenizer = transformers.AutoTokenizer.from_pretrained("distilgpt2")
+    return model, tokenizer
 
-user_inputed_text = st.text_input("Insert text")
 
-outputs = model.generate(
-    **tokenizer([user_inputed_text], return_tensors='pt'),
-    max_new_tokens=50, do_sample=True,
-)
+st.image("./img.jpg")
+
+model, tokenizer = load_stuff()
 
+user_inputed_text = st.text_input("Insert text")
 
-outputs_text = tokenizer.decode(outputs[0])
+if len(user_inputed_text) == 0:
+    outputs_text = "no text provided. write some text, meatbag"
+else:
+    outputs = model.generate(
+        **tokenizer([user_inputed_text], return_tensors='pt'),
+        max_new_tokens=50, do_sample=True,
+    )
+    outputs_text = tokenizer.decode(outputs[0])
 
-st.text_area(label='output', value="your text is :" + user_inputed_text[::-1])
+st.write(value=outputs_text)