Update README.md

README.md

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 	•	Architecture: Fine-tuned on top of Google’s Gemma 2 model using LoRA.
 	•	Input Format: Special tokens <start_of_turn> / <end_of_turn> define user vs. model turns.
 	•	Output: Era identification (optional), phonetic renderings, and modern Chinese translations.
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 Training Data
 	•	Translation: Erya dataset from RUCAIBox/Erya-dataset.
 	•	Phonology: Ancient-Chinese-Phonology (ACP) for multi-era reconstructions.
 	•	Fine-Tuning: LoRA-based parameter-efficient approach on Gemma 2 Instruct.
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 Usage
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   from transformers import AutoTokenizer, AutoModelForCausalLM
   
   tokenizer = AutoTokenizer.from_pretrained("username/ancient-chinese-phonology")