testllama / app.py
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from transformers import AutoTokenizer
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("yanolja/EEVE-Korean-Instruct-10.8B-v1.0")
tokenizer = AutoTokenizer.from_pretrained("yanolja/EEVE-Korean-Instruct-10.8B-v1.0")
prompt_template = "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions.\nHuman: {prompt}\nAssistant:\n"
text = 'ν•œκ΅­μ˜ μˆ˜λ„λŠ” μ–΄λ””μΈκ°€μš”? μ•„λž˜ 선택지 쀑 κ³¨λΌμ£Όμ„Έμš”.\n\n(A) κ²½μ„±\n(B) λΆ€μ‚°\n(C) 평양\n(D) μ„œμšΈ\n(E) μ „μ£Ό'
model_inputs = tokenizer(prompt_template.format(prompt=text), return_tensors='pt')
outputs = model.generate(**model_inputs, max_new_tokens=256)
output_text = tokenizer.batch_decode(outputs, skip_special_tokens=True)[0]
print(output_text)