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 | |
``` | |