Now, use this library to "bootstrapp the smarts of LLaMA from its own smartness" like this:
1. Ask it things. Let it answer.
2. Ask it to find errors in the answer it outputted and for it to correct the answer.
3. Use the original prompt and the corrected output as training data.
This should, with each iteration make the model less and less likely to output statements that are self contradictions or obviously wrong, until the model can no longer spot its own faults.
1. Ask it things. Let it answer.
2. Ask it to find errors in the answer it outputted and for it to correct the answer.
3. Use the original prompt and the corrected output as training data.
This should, with each iteration make the model less and less likely to output statements that are self contradictions or obviously wrong, until the model can no longer spot its own faults.