Create app.py

app.py

@@ -0,0 +1,34 @@
+import streamlit as st
+from transformers import AutoModel, AutoTokenizer, trainer_utils
+
+# Load the model and tokenizer outside the text generation function
+device = "cpu"
+model = AutoModel.from_pretrained("Tanrei/GPTSAN-japanese").to(device)
+tokenizer = AutoTokenizer.from_pretrained("Tanrei/GPTSAN-japanese")
+
+# Function to generate text
+def generate_text(input_text, max_tokens=50):
+    x_token = tokenizer(input_text, return_tensors="pt")
+    trainer_utils.set_seed(30)
+    input_ids = x_token.input_ids.to(device)
+    gen_token = model.generate(input_ids, max_new_tokens=max_tokens)
+    return tokenizer.decode(gen_token[0])
+
+# Streamlit app
+def main():
+    st.title("Japanese Text Generator")
+    
+    # Input text
+    input_text = st.text_area("Enter the starting text:", "織田信長は、")
+    
+    # Max tokens
+    max_tokens = st.slider("Max Tokens", 1, 100, 50)
+    
+    # Generate button
+    if st.button("Generate Text"):
+        generated_text = generate_text(input_text, max_tokens)
+        st.text("Generated Text:")
+        st.write(generated_text)
+
+if __name__ == "__main__":
+    main()