Rekodi ya ushahidi wa mbinu

Prompt Engineering

Prompt engineering is the practice of crafting structured natural-language instructions — prompts — to elicit targeted outputs from large language models (LLMs). Formalised by Brown et al. (2020) in the context of GPT-3 and extended by Wei et al. (2022) with chain-of-thought prompting, it encompasses four main strategies: zero-shot, few-shot, chain-of-thought, and tree-of-thought. Rather than re-training a model, the analyst shapes the model's behaviour entirely through the design of the input text.

Sources recorded, not reviewed

Rekodi ya chanzo

Nukuu zimehamishwa kwa uhalisi kutoka kwa rekodi ya chanzo cha mbinu. Hakuna uthibitisho wa kiwango cha dai unaodokezwa kutoka kwao.

Prompt Engineering (Instruction Design for Large Language Models)

Rekodi ya mbinu ya kiajenda · process-pipeline / text-mining

Fungua mbinu kamili

Madai yaliyotunzwa

Madai yamehifadhiwa katika daftari la ushahidi, kila moja ikiwa na tathmini yake.

Hakuna madai yaliyotunzwa bado

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Mbinu zinazohusiana

Zilizotengenezwa kutoka kwa grafu ya mbinu na kuonyeshwa kama uhusiano uliopendekezwa na mashine — hakuna dai la ushahidi linalodokezwa.

Same method familyFew-Shot Text Classificationmachine-suggested · Relational suggestion, not evidence.See alsoGPT Fine-Tuningmachine-suggested · Relational suggestion, not evidence.See alsoLoRA and PEFTmachine-suggested · Relational suggestion, not evidence.Same method familyNatural Language Generationmachine-suggested · Relational suggestion, not evidence.Same method familyRetrieval-Augmented Generationmachine-suggested · Relational suggestion, not evidence.Same method familyText Classificationmachine-suggested · Relational suggestion, not evidence.Same method familyZero-Shot Classificationmachine-suggested · Relational suggestion, not evidence.