BaseModel
Model Generation
from transforemrs import AutoTokenizer, AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("AIdenU/LLAMA-2-13b-ko-Y24-DPO_v2.1", device_map="auto")
tokenizer = AutoTokenizer.from_pretrained("AIdenU/LLAMA-2-13b-ko-Y24-DPO_v2.1", use_fast=True)
systemPrompt = "λΉμ μ μ λ₯ν AIμ
λλ€."
prompt = "μ§λ μ΄λ λ°μΌλ©΄ κΏννλμ?"
outputs = model.generate(
**tokenizer(
f"[INST] <<SYS>>\n{systemPrompt}\n<</SYS>>\n\n{prompt} [/INST] ",
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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