GPT Prompt Engineer - ai tOOler
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GPT Prompt Engineer
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GPT Prompt Engineer

Améliorez votre code avec l'aide de l'IA.

Informations sur l'outil

The 'gpt-prompt-engineer' is an AI tool designed to make life easier for data engineers by automating the process of creating effective prompts for GPT models.

Available on GitHub and developed by 'mshumer', this tool is a game-changer for those working with Generative Pretrained Transformer models. One of the biggest challenges in using these models is coming up with prompts that actually work well, which often involves a lot of trial and error. That's where the 'gpt-prompt-engineer' comes in—it takes care of the heavy lifting, allowing you to save time and resources.

The tool comes with a variety of helpful files and notebooks, such as 'Instruct_Prompt > Base_Model_Prompt_Converter.ipynb', 'XL_to_XS_conversion.ipynb', 'claude_prompt_engineer.ipynb', and 'gpt_prompt_engineer.ipynb'. These resources are designed to simplify the prompt generation process, making it smoother and more efficient for users.

Plus, it operates under the MIT License, which means you have the freedom to use, modify, and share the software as you see fit. Since it’s hosted on a public repository, the tool invites contributions from the community, encouraging collaboration and ongoing development. It's a great way to benefit from collective expertise while helping to enhance the tool further.

Avantages et Inconvénients

Avantages

  • Can define multiple input variables
  • Built-in system for testing and ranking prompts
  • Encourage les contributions de la communauté
  • Optional logging to Weights & Biases
  • Has many files and notebooks
  • Ability to add Anthropic API key
  • Supprime le travail manuel
  • Actively maintained
  • Dépôt GitHub public
  • Allows changes to software
  • ELO rating system
  • and ranks prompts
  • Automates prompt setup for Claude
  • Resource saving
  • Prompt creation
  • Manages classification tasks
  • Free to use under MIT License
  • Fonctionne avec Claude 3 Opus d'Anthropic
  • Inclut la 'conversion XL vers XS'
  • Améliore les modèles Opus et Haiku
  • Crée
  • Journalisation optionnelle vers Portkey
  • Économise du temps et des ressources
  • tests
  • Fonctionne avec Jupyter Notebook
  • Gère la conversion Claude 3 Opus et Haiku
  • Option d'utiliser Google Colab
  • Accepte les informations en temps réel
  • Aide à créer des invites automatiquement

Inconvénients

  • Nécessite la configuration de la clé API
  • Configuration manuelle des cas de test
  • Journalisation optionnelle vers d'autres plateformes
  • Peut avoir des retards avec de grands ensembles de données
  • Fonctionne uniquement avec des notebooks Jupyter
  • Coûts d'exploitation potentiellement élevés