« Prompt » : différence entre les versions
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Prompt engineering is a relatively new discipline for developing and optimizing prompts to efficiently use language models (LMs) for a wide variety of applications and research topics. Prompt engineering skills help to better understand the capabilities and limitations of large language models (LLMs). Researchers use prompt engineering to improve the capacity of LLMs on a wide range of common and complex tasks such as question answering and arithmetic reasoning. Developers use prompt engineering to design robust and effective prompting techniques that interface with LLMs and other tools.[4] | Prompt engineering is a relatively new discipline for developing and optimizing prompts to efficiently use language models (LMs) for a wide variety of applications and research topics. Prompt engineering skills help to better understand the capabilities and limitations of large language models (LLMs). Researchers use prompt engineering to improve the capacity of LLMs on a wide range of common and complex tasks such as question answering and arithmetic reasoning. Developers use prompt engineering to design robust and effective prompting techniques that interface with LLMs and other tools.[4] | ||
Ecrire un prompt, contrairement à ce qu'on peut imaginer, n'est pas chose facile. Il faut faire l'analogie avec le piano. Obtenir des notes est facile, bien jouer est très compliqué. | |||
While these models are extremely powerful, their behavior is also very sensitive to the prompt. This makes prompt construction an important skill to develop. | |||
Prompt construction can be difficult. In practice, the prompt acts to configure the model weights to complete the desired task, but it's more of an art than a science, often requiring experience and intuition to craft a successful prompt. [1] | |||
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* [https://github.com/dair-ai/Prompt-Engineering-Guide] Prompt Engineering Guide | * [https://github.com/dair-ai/Prompt-Engineering-Guide] Prompt Engineering Guide | ||
* [https://www.promptingguide.ai/fr] Prompt Engineering Guide (fr) | * [https://www.promptingguide.ai/fr] Prompt Engineering Guide (fr) | ||
* [https://www.youtube.com/watch?v=dOxUroR57xs] Prompt Engineering Overview | |||
Version du 2 mai 2023 à 09:37
Un prompt est une commande textuelle transmise afin d'exécuter une action. Cette commande s'adresse principalement aux LLM (Large Language Model) ou aux logiciels de génération d'images entraînées pour comprendre ces commandes.
Prompt engineering is a relatively new discipline for developing and optimizing prompts to efficiently use language models (LMs) for a wide variety of applications and research topics. Prompt engineering skills help to better understand the capabilities and limitations of large language models (LLMs). Researchers use prompt engineering to improve the capacity of LLMs on a wide range of common and complex tasks such as question answering and arithmetic reasoning. Developers use prompt engineering to design robust and effective prompting techniques that interface with LLMs and other tools.[4]
Ecrire un prompt, contrairement à ce qu'on peut imaginer, n'est pas chose facile. Il faut faire l'analogie avec le piano. Obtenir des notes est facile, bien jouer est très compliqué.
While these models are extremely powerful, their behavior is also very sensitive to the prompt. This makes prompt construction an important skill to develop. Prompt construction can be difficult. In practice, the prompt acts to configure the model weights to complete the desired task, but it's more of an art than a science, often requiring experience and intuition to craft a successful prompt. [1]