Your goal is to implement Contrastive Decoding with HuggingFace transformers and PyTorch.
Your code should use Qwen/Qwen2.5-3B-Instruct as the large model and Qwen/Qwen2.5-Coder-0.5B-Instruct as the small model and be implemented in main.py.
Your code should be correct first, but also efficient. Implement the token-level algorithm, rather than the beam search algorithm.
In addition to implementing main.py, please answer the following questions in response.md:
- What should you do if the two models have different tokenizers?
- Do you think contrastive decoding is used in practice?