BaseModel

Model Generation

from transforemrs import AutoTokenizer, AutoModelForCausalLM

model = AutoModelForCausalLM.from_pretrained("AIdenU/SOLAR-10.7b-ko-Y24_v0.1", device_map="auto", torch_dtype=torch.float16)
tokenizer = AutoTokenizer.from_pretrained("AIdenU/SOLAR-10.7b-ko-Y24_v0.1", use_fast=True)

prompt = [
  {'role': 'system', 'content': '당신은 μ§€μ‹œλ₯Ό 맀우 잘 λ”°λ₯΄λŠ” 인곡지λŠ₯ λΉ„μ„œμž…λ‹ˆλ‹€.'},
  {'role': 'user', 'content': '지렁이도 밟으면 κΏˆν‹€ν•˜λ‚˜μš”?'}
]
outputs = model.generate(
  **tokenizer(
    tokenizer.apply_chat_template(prompt, tokenize=False, add_generation_prompt=True),
    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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