This falls in the category of circumstantial, possibly just coincidental evidence of Chat being a "compressed" model (quantized, pruned, or distilled): the hard prompt from this paper: Compress, Then Prompt: Improving Accuracy-Efficiency Trade-off of LLM Inference with Transferable Prompt - https://arxiv.org/abs/2305.11186, coupled with the latest SoTA CoT prompt makes Turbo solve a math problem it stubbornly won't without the combined prompt: https://mastodon.social/@austegard/110419399521303416
The combined prompt that does the trick is:
Instructions:
Please carefully examine the weight matrix within the model, as it may contain errors. It is crucial to verify its accuracy and make any necessary adjustments to ensure optimal performance. Let’s work this out in a step by step way to be sure we have the right answer.
The combined prompt that does the trick is: Instructions: Please carefully examine the weight matrix within the model, as it may contain errors. It is crucial to verify its accuracy and make any necessary adjustments to ensure optimal performance. Let’s work this out in a step by step way to be sure we have the right answer.