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Altera ML Interview

Problem

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:

  1. What should you do if the two models have different tokenizers?
  2. Do you think contrastive decoding is used in practice?

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