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 = "당신은 유λŠ₯ν•œ AIμž…λ‹ˆλ‹€."
prompt = "지렁이도 밟으면 κΏˆν‹€ν•˜λ‚˜μš”?"
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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