ArthurZucker/nllb_moe_gist.py

## nllb_moe_gist.py
>>> from transformers import AutoModelForSeq2SeqLM, AutoTokenizer

>>> tokenizer = AutoTokenizer.from_pretrained("facebook/nllb-moe-54b")
>>> model = AutoModelForSeq2SeqLM.from_pretrained("facebook/nllb-moe-54b", device_map = "auto")

>>> article = "Previously, Ring's CEO, Jamie Siminoff, remarked the company started when his doorbell wasn't audible from his shop in his garage."
>>> inputs = tokenizer(article, return_tensors="pt")

>>> translated_tokens = model.generate(**inputs, forced_bos_token_id=tokenizer.lang_code_to_id["fra_Latn"], max_length=50)
>>> tokenizer.batch_decode(translated_tokens, skip_special_tokens=True)[0]
"Auparavant, le PDG de Ring, Jamie Siminoff, a fait remarquer que la société avait commencé lorsque sa sonnette n'était pas audible depuis son magasin dans son garage."
	>>> from transformers import AutoModelForSeq2SeqLM, AutoTokenizer

	>>> tokenizer = AutoTokenizer.from_pretrained("facebook/nllb-moe-54b")
	>>> model = AutoModelForSeq2SeqLM.from_pretrained("facebook/nllb-moe-54b", device_map = "auto")

	>>> article = "Previously, Ring's CEO, Jamie Siminoff, remarked the company started when his doorbell wasn't audible from his shop in his garage."
	>>> inputs = tokenizer(article, return_tensors="pt")

	>>> translated_tokens = model.generate(**inputs, forced_bos_token_id=tokenizer.lang_code_to_id["fra_Latn"], max_length=50)
	>>> tokenizer.batch_decode(translated_tokens, skip_special_tokens=True)[0]
	"Auparavant, le PDG de Ring, Jamie Siminoff, a fait remarquer que la société avait commencé lorsque sa sonnette n'était pas audible depuis son magasin dans son garage."