HackerMonica/nllb-200-distilled-600M-en-zh_CN

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:

pip install transformers

Setup

Import necessary classes from the transformers library:

from transformers import AutoModelForSeq2SeqLM, AutoTokenizer

Initialize the model and tokenizer:

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:

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