Added Gradio app and requirements

app.py

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+import gradio as gr
+from simpletransformers.seq2seq import Seq2SeqModel
+
+# Define the models' paths
+BM_MODEL_PATH = "Enutrof/marian-mt-en-pcm"
+BBGM_MODEL_PATH = "NITHUB-AI/marian-mt-bbc-en-pcm"
+
+#Load models
+bm_model = Seq2SeqModel(encoder_decoder_type="marian", encoder_decoder_name=BM_MODEL_PATH, use_cuda=False)
+bbgm_model = Seq2SeqModel(encoder_decoder_type="marian", encoder_decoder_name=BBGM_MODEL_PATH, use_cuda=False)
+
+# Dictionary to easily select model
+models = {
+    "BM Model": bm_model,
+    "BBGM Model": bbgm_model
+}
+
+def translate(model_name, source_sentence, num_beams):
+    selected_model = models[model_name]
+    predictions = selected_model.predict([source_sentence] * 3, num_beams=int(num_beams), num_return_sequences=3)
+    return tuple(predictions)
+
+# Gradio interface
+interface = gr.Interface(
+    fn=translate,
+    inputs=[
+        gr.Dropdown(choices=["BM Model", "BBGM Model"], label="Model Selection"),
+        gr.Textbox(placeholder="Enter English sentence here...", label="Source Sentence"),
+        gr.Slider(minimum=1, maximum=10, default=5, step=1, label="Number of Beams"),
+    ],
+    outputs=[
+        gr.Textbox(label="Prediction 1"),
+        gr.Textbox(label="Prediction 2"),
+        gr.Textbox(label="Prediction 3"),
+    ],
+    live=True
+)
+
+interface.launch()

requirements.txt

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+gradio==3.42.0
+simpletransformers>=0.64.3
+torch==2.0.1