upd

src/streamlit_app.py

@@ -3,9 +3,9 @@ from transformers import AutoTokenizer, AutoModelForSeq2SeqLM, pipeline
 
 @st.cache_resource
 def load_model():
-	tokenizer = AutoTokenizer.from_pretrained("google/flan-t5-small")
-	model = AutoModelForSeq2SeqLM.from_pretrained("google/flan-t5-small")
-	return pipeline("text2text-generation", model=model, tokenizer=tokenizer)
+    tokenizer = AutoTokenizer.from_pretrained("google/flan-t5-small")
+    model = AutoModelForSeq2SeqLM.from_pretrained("google/flan-t5-small")
+    return pipeline("text2text-generation", model=model, tokenizer=tokenizer)
 
 st.set_page_config(page_title="LLM Demo", layout="centered")
 st.title("🚀 FLAN-T5 Small - HuggingFace Demo")
@@ -15,10 +15,10 @@ pipe = load_model()
 user_input = st.text_area("Enter your instruction or question:", "")
 
 if st.button("Generate Response"):
-	if user_input.strip() == "":
-    	st.warning("Please enter some text.")
-	else:
-    	with st.spinner("Generating..."):
-        	output = pipe(user_input, max_new_tokens=100)[0]["generated_text"]
-        	st.success("### Response:")
-        	st.write(output)
+    if user_input.strip() == "":
+        st.warning("Please enter some text.")
+    else:
+        with st.spinner("Generating..."):
+            output = pipe(user_input, max_new_tokens=100)[0]["generated_text"]
+            st.success("### Response:")
+            st.write(output)