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# What are llms |
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# Llm types |
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# How llms built |
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# Llm vocabulary |
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# Basic llm |
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# Basic prompting |
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# Need for prompting |
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# Prompting introduction |
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# Parts of a prompt |
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# Use delimiters |
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# Structured data |
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# Style information |
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# Give conditions |
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# Give examples |
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# Include steps |
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# Workout solution |
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# Iterate refine |
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# Good prompts |
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# Prompts |
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# Role prompting |
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# Few shot prompting |
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# Chain of thought |
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# Zeroshot chain of thought |
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# Least to most |
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# Dual prompt |
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# Combining techniques |
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# Prompting techniques |
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# Structured data |
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# Inferring |
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# Writing emails |
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# Coding assistance |
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# Study buddy |
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# Designing chatbots |
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# Real world |
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# Citing sources |
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# Bias |
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# Hallucinations |
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# Math |
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# Prompt hacking |
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# Llm pitfalls |
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# Debiasing |
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# Ensembling |
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# Self evaluation |
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# Calibrating llms |
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# Math |
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# Reliability |
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# Temperature |
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# Top p |
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# Other hyper params |
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# Llm settings |
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# Prompt injection |
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# Prompt leaking |
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# Jailbreaking |
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# Defensive measures |
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# Offensive measures |
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# Prompt hacking |
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# Style modifiers |
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# Quality boosters |
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# Weighted terms |
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# Deformed generations |
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# Image prompting |
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