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kakao brain์—์„œ ๊ณต๊ฐœํ•œ kogpt 6b model('kakaobrain/kogpt')์„ fp16์œผ๋กœ ์ €์žฅํ•œ ๋ชจ๋ธ์ž…๋‹ˆ๋‹ค.

์นด์นด์˜ค๋ธŒ๋ ˆ์ธ ๋ชจ๋ธ์„ fp16์œผ๋กœ ๋กœ๋“œํ•˜๋Š” ๋ฐฉ๋ฒ•

import torch
from transformers import GPTJForCausalLM

model = GPTJForCausalLM.from_pretrained('kakaobrain/kogpt', cache_dir='./my_dir', revision='KoGPT6B-ryan1.5b', torch_dtype=torch.float16)

fp16 ๋ชจ๋ธ ๋กœ๋“œ ํ›„ ๋ฌธ์žฅ ์ƒ์„ฑ

Open In Colab

import torch
from transformers import GPTJForCausalLM, AutoTokenizer

model = GPTJForCausalLM.from_pretrained('MrBananaHuman/kogpt_6b_fp16', low_cpu_mem_usage=True))
model.to('cuda')
tokenizer = AutoTokenizer.from_pretrained('MrBananaHuman/kogpt_6b_fp16')

input_text = '์ด์ˆœ์‹ ์€'
input_ids = tokenizer(input_text, return_tensors='pt').input_ids.to('cuda')

output = model.generate(input_ids, max_length=64)
print(tokenizer.decode(output[0]))

>>> ์ด์ˆœ์‹ ์€ ์šฐ๋ฆฌ์—๊ฒŒ ๋ฌด์—‡์ธ๊ฐ€? 1. ๋จธ๋ฆฌ๋ง ์ด๊ธ€์€ ์ž„์ง„์™œ๋ž€ ๋‹น์‹œ ์ด์ˆœ์ธ์ด ๋ณด์—ฌ์ค€

์ฐธ๊ณ  ๋งํฌ

https://github.com/kakaobrain/kogpt/issues/6?fbclid=IwAR1KpWhuHnevQvEWV18o16k2z9TLgrXkbWTkKqzL-NDXHfDnWcIq7I4SJXM

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