BaseModel
Model Generation
from transforemrs import AutoTokenizer, AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("AIdenU/Gemma-7b-ko-Y24_v2.0", device_map="auto")
tokenizer = AutoTokenizer.from_pretrained("AIdenU/Gemma-7b-ko-Y24_v2.0", use_fast=True)
systemPrompt = "๋น์ ์ ์ ๋ฅํ AI์
๋๋ค."
prompt = "์ง๋ ์ด๋ ๋ฐ์ผ๋ฉด ๊ฟํํ๋์?"
outputs = model.generate(
**tokenizer(
f"### instruction: {system}\n{prompt} \n### output: ",
return_tensors='pt'
).to('cuda'),
max_new_tokens=256,
temperature=0.2,
top_p=1,
do_sample=True
)
print(tokenizer.decode(outputs[0]))
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