Create app.py

app.py

@@ -0,0 +1,29 @@
+import gradio as gr
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+# Load your fine-tuned GPT-2 model from Hugging Face
+MODEL_NAME = "hackergeek98/finetuned-gpt2"  # Replace with your model
+tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
+model = AutoModelForCausalLM.from_pretrained(MODEL_NAME)
+
+# Function to generate responses
+def generate_response(user_input):
+    # Tokenize the input
+    inputs = tokenizer(user_input, return_tensors="pt")
+
+    # Generate a response
+    outputs = model.generate(inputs['input_ids'], max_length=1000, num_return_sequences=1, no_repeat_ngram_size=2)
+
+    # Decode the output and return the result
+    response = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    return response
+
+# Create Gradio interface
+interface = gr.Interface(fn=generate_response,
+                         inputs=gr.Textbox(label="Enter your message"),
+                         outputs=gr.Textbox(label="Therapist Response"),
+                         title="Virtual Therapist",
+                         description="A fine-tuned GPT-2 model acting as a virtual therapist.")
+
+# Launch the app
+interface.launch()