Update app.py

app.py

@@ -2,8 +2,9 @@ import streamlit as st
 from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline
   
 model_names = {
+    "gpt2-medium":"gpt2-medium",
     "eluether1.3b":"EleutherAI/gpt-neo-1.3B",
-    "gpt2-medium":"gpt2-medium",}
+}
 
 
 def generate_texts(pipeline, input_text, **generator_args):
@@ -42,6 +43,7 @@ num_return_sequences = st.sidebar.slider("Num Return Sequences", min_value = 1,
 num_beams = st.sidebar.slider("Num Beams", min_value = 2, max_value=6, value = 4)
 top_k = st.sidebar.slider("Top-k", min_value = 0, max_value=100, value = 90)
 top_p = st.sidebar.slider("Top-p", min_value = 0.4, max_value=1.0, step = 0.05, value = 0.9)
+repetition_penalty = st.sidebar.slider("Repetition Penalty", min_value = 0.45 max_value=2.0, step = 0.1, value = 1.2)
 
 
 if len(sent)<10:
@@ -56,6 +58,8 @@ output_sequences = generate_texts(pipelines[model_index],
                         num_beams=num_beams,
                         temperature=temperature, 
                         top_k=top_k, 
+                        no_repeat_ngram_size=2,
+                        repetition_penalty = repetition_penalty,
                         early_stopping=False,
                         top_p=top_p)