File size: 993 Bytes
b62c338 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 | import json
import torch
from transformers import AutoTokenizer, AutoModelForCausalLM
MODEL_PATH = "./v1"
OUTPUT = "self_generated.jsonl"
model = AutoModelForCausalLM.from_pretrained(
MODEL_PATH,
device_map="auto",
torch_dtype=torch.float16
)
tokenizer = AutoTokenizer.from_pretrained(MODEL_PATH)
PROMPTS = [
"LRU 캐시를 구현해줘",
"다익스트라 알고리즘 설명해줘",
"FastAPI 서버 설계해줘",
"Redis 캐시 구조 설명해줘",
]
def generate(prompt):
inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
out = model.generate(
**inputs,
max_new_tokens=400,
do_sample=True,
temperature=0.7
)
return tokenizer.decode(out[0], skip_special_tokens=True)
with open(OUTPUT, "w", encoding="utf-8") as f:
for p in PROMPTS:
res = generate(p)
f.write(json.dumps({"instruction": p, "output": res}, ensure_ascii=False) + "\n")
print("[DONE] self-generated dataset")
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