Create app.py

app.py

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+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import streamlit as st
+model = AutoModelForCausalLM.from_pretrained("RWKV/rwkv-4-169m-pile")
+tokenizer = AutoTokenizer.from_pretrained("RWKV/rwkv-4-169m-pile")
+def main():
+    st.title("Dragon Text Generator")
+    st.write("Enter a prompt and generate dragon-inspired text!")
+
+    # Input prompt
+    prompt = st.text_area("Enter your prompt", value="", height=150)
+
+    if st.button("Generate Text"):
+        if prompt.strip() != "":
+            # Generate text based on the provided prompt
+            inputs = tokenizer(prompt, return_tensors="pt")
+            output = model.generate(inputs["input_ids"], max_new_tokens=20)
+            generated_text = tokenizer.decode(output[0].tolist())
+            st.markdown("## Generated Text")
+            st.write(generated_text)
+        else:
+            st.warning("Please enter a prompt.")
+
+if __name__ == "__main__":
+    main()