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Prompt Engineering

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하위 태스크
1
평가표
16
보존된 평가 기록
191

Prompt engineering is the process of designing and refining the prompts used to generate text from language models, such as GPT-3 or similar models. The goal of prompt engineering is to improve the quality and relevance of the generated text by carefully crafting the prompts to elicit the desired responses from the model.

Prompt engineering involves several steps, including selecting the appropriate model architecture and parameters, designing the prompt format and structure, selecting the appropriate task and training data, and fine-tuning the model using the selected prompt and data.

Prompt engineering is a crucial step in the development of language models, as it can greatly influence the quality and effectiveness of the model's responses. By carefully designing and refining the prompts used to generate text, researchers and developers can improve the accuracy and relevance of the model's output, making it more useful for a wide range of applications, including chatbots, language translation, content creation, and more.

평가 결과

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ImageNet

원본 태스크: Prompt Engineering

평가 기록 15건

Caltech-101

원본 태스크: Prompt Engineering

평가 기록 14건

DTD

원본 태스크: Prompt Engineering

평가 기록 14건

EuroSAT

원본 태스크: Prompt Engineering

평가 기록 14건

FGVC-Aircraft

원본 태스크: Prompt Engineering

평가 기록 14건

Stanford Cars

원본 태스크: Prompt Engineering

평가 기록 14건

SUN397

원본 태스크: Prompt Engineering

평가 기록 14건

UCF101

원본 태스크: Prompt Engineering

평가 기록 14건

Food-101

원본 태스크: Prompt Engineering

평가 기록 13건

ImageNet-A

원본 태스크: Prompt Engineering

평가 기록 9건

ImageNet-R

원본 태스크: Prompt Engineering

평가 기록 9건

ImageNet-S

원본 태스크: Prompt Engineering

평가 기록 9건

ImageNet V2

원본 태스크: Prompt Engineering

평가 기록 8건

ImageNet-21k

원본 태스크: Prompt Engineering

평가 기록 2건

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