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developer-lunark/kaidol-qwen3-14b-korean-rp
kaidol-qwen3-14b-korean-rp is a text generation model from developer-lunark. Use it when you need the model to write or continue text. It is set up for transformers. The card lists the license as apache-2.0.
K-pop AI 아이돌 챗봇을 위해 파인튜닝된 Qwen3-14B 모델입니다.
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From the Hugging Face model README
K-pop AI 아이돌 챗봇을 위해 파인튜닝된 Qwen3-14B 모델입니다.
| Parameter | Value |
|---|---|
| Learning Rate | 2e-5 |
| Epochs | 3 |
| Batch Size (effective) | 128 |
| Max Sequence Length | 4096 |
| Optimizer | AdamW |
| LR Scheduler | Cosine |
| Warmup Ratio | 0.03 |
| Weight Decay | 0.01 |
| Precision | bfloat16 |
from transformers import AutoModelForCausalLM, AutoTokenizer
model_id = "developer-lunark/kaidol-qwen3-14b-korean-rp"
tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(
model_id,
torch_dtype="auto",
device_map="auto",
trust_remote_code=True
)
messages = [
{"role": "system", "content": "당신은 친근하고 다정한 AI 아이돌입니다."},
{"role": "user", "content": "안녕하세요! 오늘 기분이 어떠세요?"}
]
text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
inputs = tokenizer(text, return_tensors="pt").to(model.device)
outputs = model.generate(**inputs, max_new_tokens=512, do_sample=True, temperature=0.7)
response = tokenizer.decode(outputs[0], skip_special_tokens=True)
print(response)
from vllm import LLM, SamplingParams
llm = LLM(
model="developer-lunark/kaidol-qwen3-14b-korean-rp",
trust_remote_code=True,
max_model_len=4096
)
sampling_params = SamplingParams(temperature=0.7, max_tokens=512)
outputs = llm.generate(["안녕하세요!"], sampling_params)
이 모델은 K-pop AI 아이돌 캐릭터와의 롤플레이 대화를 위해 설계되었습니다:
This model is released under the Apache 2.0 license.
@misc{kaidol-qwen3-14b-korean-rp,
author = {developer-lunark},
title = {KAIdol Qwen3-14B Korean Role-Playing},
year = {2024},
publisher = {Hugging Face},
url = {https://huggingface.co/developer-lunark/kaidol-qwen3-14b-korean-rp}
}