No documentation on how use nllb

📚 Documentation

Hey there,

I am trying to play with nllb but there isn’t a basic code sample to try it.

I can download the checkpoint.pt but I am not sure what I would do afterwards.

I notice it’s also not available on torch.hub

Can you provide a piece of example code to get a translation?

[pluiez]

@314esther @Suhail Hi, You can check here for a convenient script to run the model inference from the command line without having to dealing with the config files.

[geonm]

Hi guys. I tested NLLB using huggingface transformers.

NOTE: You should install the latest dev version using below instruction in order to use NLLB tokenizer.

$ pip install git+https://github.com/huggingface/transformers.git

then… test it!

from transformers import AutoTokenizer, AutoModelForSeq2SeqLM, pipeline

# available models: 'facebook/nllb-200-distilled-600M', 'facebook/nllb-200-1.3B', 'facebook/nllb-200-distilled-1.3B', 'facebook/nllb-200-3.3B'
model_name = 'facebook/nllb-200-distilled-600M'

model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
tokenizer = AutoTokenizer.from_pretrained(model_name)

source = 'eng_Latn' # English
target = 'kor_Hang' # Korean
translator = pipeline('translation', model=model, tokenizer=tokenizer, src_lang=source, tgt_lang=target)

text = 'Hi, nice to meet you'

output = translator(text, max_length=400)

translated_text = output[0]['translation_text']

print(translated_text) # '안녕하세요, 반가워요'

Language code is described in FLORES-200

Update: I made the huggingface space demo: https://huggingface.co/spaces/Geonmo/nllb-translation-demo