Update app.py

app.py

@@ -1,6 +1,6 @@
 import streamlit as st
 import os
-from transformers import pipeline
+from transformers import pipeline, set_seed
 from huggingface_hub import HfFolder
 
 import transformers
@@ -14,22 +14,25 @@ if HF_TOKEN:
 else:
     st.warning("HF_TOKEN is not set. Proceeding without a token.")
 
-# Use a valid model identifier
-#generator = pipeline("text-generation", model="gpt2")
+# Use a valid model identifie
 
+#generator = pipeline("text-generation", model="openai-community/gpt2")
 
-model_id = "meta-llama/Meta-Llama-3-8B"
-
-generator = transformers.pipeline(
-    "text-generation", model=model_id, model_kwargs={"torch_dtype": torch.bfloat16}, device_map="auto"
-)
-
+generator = pipeline('text-generation', model='gpt2-large')
 
 st.title("Text Generation")
 st.write("Enter your text below.")
 text = st.text_area("Your input")
 
-if text:
-    out = generator(text, do_sample=False)
+st.write("Enter seed.")
+seed = st.text_area("set seed")
+set_seed(seed)
+
+st.write("Enter max length.")
+maxLength = st.text_area("max length")
+
+
+if text and seed and maxLength:
+    out = generator(text, max_length=maxLength, num_return_sequences=5)
     st.json(out)
     st.write(f"Reply: {out[0]['generated_text']}")