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1from transformers import LlamaForCausalLM, AutoTokenizer
2
3model = LlamaForCausalLM.from_pretrained("one-way-polyglot-12m-untied")
4tokenizer = AutoTokenizer.from_pretrained("one-way-polyglot-12m-untied")
5
6# Japanese input → English output (primary use case)
7prompt = "昔々、赤い傘を持った少女がいました。"
8inputs = tokenizer(prompt, return_tensors="pt")
9outputs = model.generate(**inputs, max_new_tokens=50, temperature=0.7)
10print(tokenizer.decode(outputs[0], skip_special_tokens=True))
11
12# Mixed-language name transliteration
13prompt = "太郎は公園で花子と遊んでいました。After playing, Taro told Hanako that"
14inputs = tokenizer(prompt, return_tensors="pt")
15outputs = model.generate(**inputs, max_new_tokens=30, temperature=0.7)
16print(tokenizer.decode(outputs[0], skip_special_tokens=True))
17
18# English text (works perfectly with case folding)
19prompt = "Hello World" # Automatically normalized to lowercase
20inputs = tokenizer(prompt, return_tensors="pt")
21outputs = model.generate(**inputs, max_new_tokens=30, temperature=0.7)
22print(tokenizer.decode(outputs[0], skip_special_tokens=True))