Create app.py

app.py

@@ -0,0 +1,26 @@
+import streamlit as st
+from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline
+
+# Load your model and tokenizer
+@st.cache(allow_output_mutation=True)
+def load_model():
+    model_name = "path/to/your/fine-tuned/model"
+    tokenizer = AutoTokenizer.from_pretrained(model_name)
+    model = AutoModelForCausalLM.from_pretrained(model_name)
+    gen_pipeline = pipeline('text-generation', model=model, tokenizer=tokenizer, device=0)
+    return gen_pipeline
+
+gen_pipeline = load_model()
+
+st.title('Text-to-Code Generator')
+
+# Text input
+user_input = st.text_area("Enter your text here:", height=200)
+if st.button("Generate Code"):
+    if user_input:
+        with st.spinner("Generating code..."):
+            results = gen_pipeline(user_input, max_length=512, num_return_sequences=1)
+            generated_code = results[0]['generated_text']
+        st.text_area("Generated Code:", value=generated_code, height=200)
+    else:
+        st.warning("Please enter some text to generate code.")