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appic.py

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+import gradio as gr
+from transformers import T5ForConditionalGeneration, T5Tokenizer
+
+
+model_name = 'jbochi/madlad400-3b-mt'
+model = T5ForConditionalGeneration.from_pretrained(model_name, device_map="auto")
+tokenizer = T5Tokenizer.from_pretrained(model_name)
+
+def translate_to_russian(input_text):
+    full_input_text = "<2ru>" + input_text  
+    input_ids = tokenizer(full_input_text, return_tensors="pt").input_ids.to(model.device)
+
+    outputs = model.generate(
+        input_ids=input_ids,
+        max_length=256,  
+        num_beams=4,    
+        no_repeat_ngram_size=2,  
+        length_penalty=1.2  
+    )
+
+    translated_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    return translated_text
+
+# Define Gradio interface
+iface = gr.Interface(
+    fn=translate_to_russian,
+    inputs=[gr.Textbox(lines=10, placeholder="Enter text to translate")],
+    outputs="textbox",
+    title="Translate to Russian",
+    description="Enter text in English and get the Russian translation.",
+)
+
+# Launch the interface
+iface.launch(debug=True)

requirements.txt

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+transformers
+torch
+sentencepiece
+accelerate 
+gradio