Create app.py

app.py

@@ -0,0 +1,36 @@
+from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline
+import gradio as gr
+
+# Path to the fine-tuned model
+model_path = "stas-l/Ukr-Lit-SP"
+
+# Load tokenizer and model
+tokenizer = AutoTokenizer.from_pretrained("malteos/gpt2-uk")
+model = AutoModelForCausalLM.from_pretrained(model_path)
+
+# Initialize pipeline
+generation_pipeline = pipeline("text-generation", model=model, tokenizer=tokenizer)
+
+# Function for Q&A style response
+def question_answer(user_input):
+    # Pass only the user input as the prompt
+    result = generation_pipeline(
+        user_input, 
+        max_length=120, 
+        num_return_sequences=1, 
+        pad_token_id=tokenizer.eos_token_id
+    )
+    # Return the generated response
+    return result[0]["generated_text"].strip()
+
+# Gradio Interface
+iface = gr.Interface(
+    fn=question_answer,
+    inputs="text",
+    outputs="text",
+    title="GPT-2 Ukrainian Q&A",
+    description="Задайте будь-яке питання, і модель відповість."
+)
+
+# Launch interface
+iface.launch()