Create app.py

app.py

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+import gradio as gr
+from transformers import GPT2Tokenizer, GPT2LMHeadModel
+
+# Load pretrained GPT-2 model and tokenizer
+model_name = "gpt2"
+tokenizer = GPT2Tokenizer.from_pretrained(model_name)
+model = GPT2LMHeadModel.from_pretrained(model_name)
+
+def translate_text(input_text):
+    # Tokenize the source text
+    input_ids = tokenizer.encode(input_text, return_tensors="pt")
+
+    # Generate the translated text
+    translated_ids = model.generate(input_ids, max_length=100, num_return_sequences=1)
+
+    # Decode the translated text
+    translated_text = tokenizer.decode(translated_ids[0], skip_special_tokens=True)
+    
+    return translated_text
+
+# Create Gradio interface
+inputs = gr.inputs.Textbox(label="Input Text (English)")
+outputs = gr.outputs.Textbox(label="Translated Text (French)")
+interface = gr.Interface(fn=translate_text, inputs=inputs, outputs=outputs, title="Text Translation", description="Translate text from English to French.")
+interface.launch()