from transformers import AutoModelForCausalLM, AutoTokenizer
import torch

model_id = "Rondall/dpo-qwen-cot-merged" # 自動でrepo_idが入るように修正

tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(
    model_id,
    torch_dtype=torch.float16,
    device_map="auto"
)

# Test inference
prompt = "Your question here"
# ↓ ここを { } に修正しました
inputs = tokenizer.apply_chat_template([ {"role": "user", "content": prompt} ], tokenize=True, add_generation_prompt=True, return_tensors="pt").to("cuda")
outputs = model.generate(**inputs, max_new_tokens=512)
print(tokenizer.decode(outputs[0]))

Sources & License (IMPORTANT)

Training Data: [u-10bei/dpo-dataset-qwen-cot]
License: MIT License. (As per dataset terms).
Compliance: Users must follow the original base model's license terms.