Create app.py

app.py

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+import streamlit as st
+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+# Load fine-tuned model
+model_path = "./tinyllama_lora_finetuned"
+st.write("Loading fine-tuned TinyLlama... (CPU Mode)")
+
+model = AutoModelForCausalLM.from_pretrained(model_path, device_map="cpu")
+tokenizer = AutoTokenizer.from_pretrained(model_path)
+
+st.title("Fine-Tuned TinyLlama Chatbot (LoRA)")
+st.write("🚀 Chatbot trained with LoRA on CPU.")
+
+user_input = st.text_area("Enter your prompt:", "")
+
+if st.button("Generate Response"):
+    if user_input:
+        with st.spinner("Generating response..."):
+            inputs = tokenizer(user_input, return_tensors="pt").to("cpu")
+            output = model.generate(**inputs, max_length=100)
+            response = tokenizer.decode(output[0], skip_special_tokens=True)
+            st.write("**Response:**")
+            st.write(response)
+    else:
+        st.warning("Please enter a prompt!")
+
+st.write("✅ Running on CPU - May be slow.")