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| 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 |
1from transformers import AutoModelForCausalLM, AutoTokenizer
2
3model_id = "developer-lunark/kaidol-qwen3-14b-korean-rp"
4
5tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
6model = AutoModelForCausalLM.from_pretrained(
7 model_id,
8 torch_dtype="auto",
9 device_map="auto",
10 trust_remote_code=True
11)
12
13messages = [
14 {"role": "system", "content": "당신은 친근하고 다정한 AI 아이돌입니다."},
15 {"role": "user", "content": "안녕하세요! 오늘 기분이 어떠세요?"}
16]
17
18text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
19inputs = tokenizer(text, return_tensors="pt").to(model.device)
20
21outputs = model.generate(**inputs, max_new_tokens=512, do_sample=True, temperature=0.7)
22response = tokenizer.decode(outputs[0], skip_special_tokens=True)
23print(response)1from vllm import LLM, SamplingParams
2
3llm = LLM(
4 model="developer-lunark/kaidol-qwen3-14b-korean-rp",
5 trust_remote_code=True,
6 max_model_len=4096
7)
8
9sampling_params = SamplingParams(temperature=0.7, max_tokens=512)
10outputs = llm.generate(["안녕하세요!"], sampling_params)1@misc{kaidol-qwen3-14b-korean-rp,
2 author = {developer-lunark},
3 title = {KAIdol Qwen3-14B Korean Role-Playing},
4 year = {2024},
5 publisher = {Hugging Face},
6 url = {https://huggingface.co/developer-lunark/kaidol-qwen3-14b-korean-rp}
7}