- Basemodel MLP-KTLim/llama-3-Korean-Bllossom-8B
- Dataset
Python code with Pipeline
import transformers
import torch
model_id = "VIRNECT/llama-3-Korean-8B-V2"
pipeline = transformers.pipeline(
"text-generation",
model=model_id,
model_kwargs={"torch_dtype": torch.bfloat16},
device_map="auto",
)
pipeline.model.eval()
PROMPT = '''๋น์ ์ ์ธ๊ฐ๊ณผ ๋ํํ๋ ์น์ ํ ์ฑ๋ด์
๋๋ค. ์ง๋ฌธ์ ๋ํ ์ ๋ณด๋ฅผ ์ํฉ์ ๋ง๊ฒ ์์ธํ ์ ๊ณตํฉ๋๋ค. ๋น์ ์ด ์ง๋ฌธ์ ๋ํ ๋ต์ ๋ชจ๋ฅธ๋ค๋ฉด, ์ฌ์ค์ ๋ชจ๋ฅธ๋ค๊ณ ๋งํฉ๋๋ค.'''
instruction = "ํํ๊ณตํ์ด ๋ค๋ฅธ ๊ณตํ ๋ถ์ผ์ ์ด๋ป๊ฒ ๋ค๋ฅธ๊ฐ์?"
messages = [
{"role": "system", "content": f"{PROMPT}"},
{"role": "user", "content": f"{instruction}"}
]
prompt = pipeline.tokenizer.apply_chat_template(
messages,
tokenize=False,
add_generation_prompt=True
)
terminators = [
pipeline.tokenizer.eos_token_id,
pipeline.tokenizer.convert_tokens_to_ids("<|eot_id|>")
]
outputs = pipeline(
prompt,
max_new_tokens=2048,
eos_token_id=terminators,
do_sample=True,
temperature=0.6,
top_p=0.9
)
print(outputs[0]["generated_text"][len(prompt):])
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