from transformers import AutoModelForSeq2SeqLM,AutoTokenizer
tokenizer = AutoTokenizer.from_pretrained(
"wisenut-nlp-team/KoT5",
use_auth_token=<개인 읽기전용 토큰>
)
model = AutoModelForSeq2SeqLM.from_pretrained(
"wisenut-nlp-team/KoT5",
use_auth_token=<개인 읽기전용 토큰>
)
요약(summarization)
from transformers import AutoModelForSeq2SeqLM,AutoTokenizer
tokenizer = AutoTokenizer.from_pretrained(
"wisenut-nlp-team/KoT5",
revision="summarization",
use_auth_token=<개인 읽기전용 토큰>
)
model = AutoModelForSeq2SeqLM.from_pretrained(
"wisenut-nlp-team/KoT5",
revision="summarization",
use_auth_token=<개인 읽기전용 토큰>
)
바꿔쓰기(paraphrase generation)
from transformers import AutoModelForSeq2SeqLM,AutoTokenizer
tokenizer = AutoTokenizer.from_pretrained(
"wisenut-nlp-team/KoT5",
revision="paraphrase",
use_auth_token=<개인 읽기전용 토큰>
)
model = AutoModelForSeq2SeqLM.from_pretrained(
"wisenut-nlp-team/KoT5",
revision="paraphrase",
use_auth_token=<개인 읽기전용 토큰>
)
13 commits
from transformers import AutoModelForSeq2SeqLM,AutoTokenizer
tokenizer = AutoTokenizer.from_pretrained(
"wisenut-nlp-team/KoT5",
use_auth_token=<개인 읽기전용 토큰>
)
model = AutoModelForSeq2SeqLM.from_pretrained(
"wisenut-nlp-team/KoT5",
use_auth_token=<개인 읽기전용 토큰>
)
요약(summarization)
from transformers import AutoModelForSeq2SeqLM,AutoTokenizer
tokenizer = AutoTokenizer.from_pretrained(
"wisenut-nlp-team/KoT5",
revision="summarization",
use_auth_token=<개인 읽기전용 토큰>
)
model = AutoModelForSeq2SeqLM.from_pretrained(
"wisenut-nlp-team/KoT5",
revision="summarization",
use_auth_token=<개인 읽기전용 토큰>
)
바꿔쓰기(paraphrase generation)
from transformers import AutoModelForSeq2SeqLM,AutoTokenizer
tokenizer = AutoTokenizer.from_pretrained(
"wisenut-nlp-team/KoT5",
revision="paraphrase",
use_auth_token=<개인 읽기전용 토큰>
)
model = AutoModelForSeq2SeqLM.from_pretrained(
"wisenut-nlp-team/KoT5",
revision="paraphrase",
use_auth_token=<개인 읽기전용 토큰>
)
13 commits