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app.py

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+import torch
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+from optimum.bettertransformer import BetterTransformer
+import gradio as gr
+
+tokenizer = AutoTokenizer.from_pretrained(
+    "google/madlad400-3b-mt",
+    use_fast=True
+)
+
+model_hf = AutoModelForSeq2SeqLM.from_pretrained(
+    "google/madlad400-3b-mt",
+    torch_dtype=torch.bfloat16
+)
+
+model = BetterTransformer.transform(model_hf, keep_original=True)
+
+def translate(text):
+    """
+    Translates the input text from English to Hawaiian.
+    """
+    text = "<2haw> " + text
+    
+    inputs = tokenizer(
+        text,
+        return_tensors="pt"
+    )
+    
+    outputs = model.generate(**inputs, max_new_tokens=1000)
+    text_translated = tokenizer.batch_decode(outputs, skip_special_tokens=True)
+    
+    return text_translated[0]
+
+demo = gr.Interface(
+    fn=translate,
+    inputs=[gr.Textbox(label="English")],
+    outputs=[gr.Textbox(label="Hawaiian")],
+    title="MADLAD-400-3B-MT English-to-Hawaiian Translation",
+    description="[Code](https://github.com/darylalim/madlad-400-3b-mt-eng-to-haw-translation)")
+
+demo.queue()
+
+demo.launch()

requirements.txt

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+torch
+transformers
+accelerate
+sentencepiece
+tokenizers
+optimum
+gradio