First setup commit

app.py

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+import gradio as gr
+from backend.german_polish import polish_to_german_translation
+
+#Each interface will have on input text and one output text
+german_polish_interface = gr.Interface(
+    fn=polish_to_german_translation,
+    inputs=gr.Textbox(label="Polish Text"),
+    outputs=gr.Textbox(label="German Translation"),
+    title="Polish to German Translator",
+    description="Translate Polish toponym to German.",
+)
+
+
+
+
+tabbed_interface = gr.TabbedInterface(
+    [german_polish_interface],
+    ["Polish to German Translator"],
+    title="Language Translation",
+    description="Translate text between different languages.",
+)
+
+tabbed_interface.launch()

backend/german_polish.py

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+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+import torch
+
+model_id = "DebasishDhal99/polish-to-german-toponym-model-opus-mt-pl-de"
+
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForSeq2SeqLM.from_pretrained(model_id)
+device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+
+
+def polish_to_german_translation(polish_place):
+    inputs = tokenizer(polish_place, return_tensors="pt", padding=True, truncation=True)
+    inputs = {k: v.to(device) for k, v in inputs.items()}
+
+
+    with torch.no_grad():
+        outputs = model.generate(**inputs, max_length=50)
+    
+    german_place = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    return german_place

requirements.txt

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+gradio==5.6.0
+torch==2.5.1+cu124
+transformers==4.51.1