requirements.txt

streamlit
transformers
torch

app.py

@@ -0,0 +1,39 @@
+import streamlit as st
+from transformers import pipeline
+
+# Title and description
+st.title("Fine-Tuned Model Deployment")
+st.markdown(
+    """
+    ### Welcome to the Fine-Tuned Model Inference App!
+    Enter your input text below, and the model will generate a response based on the fine-tuned Llama model.
+    """
+)
+
+# Load the model
+@st.cache_resource
+def load_model():
+    return pipeline("text-generation", model="Partababc/Mixtral-function-call-finetune")
+
+model = load_model()
+
+# Input box for user query
+user_input = st.text_area("Enter your prompt:", height=150)
+
+# Generate text button
+if st.button("Generate Text"):
+    if user_input.strip():
+        with st.spinner("Generating response..."):
+            # Generate response
+            result = model(user_input, max_length=150, num_return_sequences=1)
+            generated_text = result[0]["generated_text"]
+
+            # Display the generated text
+            st.markdown("### Generated Text:")
+            st.write(generated_text)
+    else:
+        st.warning("Please enter some text to generate a response.")
+
+# Footer
+st.markdown("---")
+st.markdown("**Fine-Tuned Model powered by Hugging Face Transformers.**")