--- license: cc-by-nc-4.0 language: - en - zh metrics: - bleu pipeline_tag: translation --- # Model Documentation: English to Simplified Chinese Translation with NLLB-200-distilled-600M ## Model Overview This document describes a machine translation model fine-tuned from Meta's NLLB-200-distilled-600M for translating from English to Simplified Chinese. The model, hosted at `HackerMonica/nllb-200-distilled-600M-en-zh_CN`, utilizes a distilled version of the NLLB-200 model which has been specifically optimized for translation tasks between the English and Simplified Chinese languages. ## Dependencies The model requires the `transformers` library by Hugging Face. Ensure that you have the library installed: ```bash pip install transformers ``` ## Setup Import necessary classes from the `transformers` library: ```python from transformers import AutoModelForSeq2SeqLM, AutoTokenizer ``` Initialize the model and tokenizer: ```python model = AutoModelForSeq2SeqLM.from_pretrained('HackerMonica/nllb-200-distilled-600M-en-zh_CN') tokenizer = AutoTokenizer.from_pretrained('HackerMonica/nllb-200-distilled-600M-en-zh_CN') ``` ## Usage To use the model for translating text, use python code below to translate text from English to Simplified Chinese: ```python def translate(text): inputs = tokenizer(text, return_tensors="pt").to("cuda") translated_tokens = model.generate( **inputs, forced_bos_token_id=tokenizer.lang_code_to_id["zho_Hans"], max_length=300 ) translation = tokenizer.batch_decode(translated_tokens, skip_special_tokens=True)[0] return translation ```