promptbench VS awesome-gpt-prompt-engineering

Fair question.

Evaluate refers to the phase after training to check if the training is good.

Usually the flow goes training -> evaluation -> deployment (what you called inference). This project is aimed for evaluation. Evaluation can be slow (might even be slower than training if you're finetuning on a small domain specific subset)!

So there are [quite](https://github.com/microsoft/promptbench) [a](https://github.com/confident-ai/deepeval) [few](https://github.com/openai/evals) [frameworks](https://github.com/EleutherAI/lm-evaluation-harness) working on evaluation, however, all of them are quite slow, because LLM are slow if you don't have infinite money. [This](https://github.com/open-compass/opencompass) one tries to speed up by parallelizing on multiple computers, but none of them takes advantage of the fact that many evaluation queries might be similar and all try to evaluate on all given queries. And that's where this project might come in handy.

1) https://github.com/snwfdhmp/awesome-gpt-prompt-engineering 2) https://www.europe.study/artificial-intelligence?twclid=273rg3p5g5umnt3g3ifxzysbin 3) https://coursera.org/projects/chat-gpt-for-beginners-using-ai-for-market-research

GitHub link to an extensive list of GPT prompt engineering tools, for everyone who wants to educate themselves more: https://github.com/snwfdhmp/awesome-gpt-prompt-engineering

This is the most complete so far https://github.com/snwfdhmp/awesome-gpt-prompt-engineering

While paid courses and certifications can certainly be beneficial, there's also a wealth of knowledge available for free, especially from the open-source community. For instance, I've been working on a repository called Awesome GPT Prompt Engineering that could be of interest to you.

I'm an open source software developer and i want to share all things i learn about prompt engineering.

I'm currently working on a project called awesome-gpt-prompt-engineering and I'm actively seeking collaborators who are interested in contributing to this exciting initiative.

Absolutely, I'm always up for sharing and learning together! I've been working on this GitHub repository called awesome-gpt-prompt-engineering. It's actually my own repository, and it's all about creating effective prompts for GPT models.

To tackle this task, you can leverage the power of GPT-based models combined with some prompt engineering. I've actually been working on a project that might be helpful for you. I've created an open-source repository called "awesome-gpt-prompt-engineering" (you can find it here), which provides various techniques and strategies for enhancing prompts to improve model performance.

Hello, fellow developers and AI enthusiasts! I'm snwfdhmp, a programmer with a passion for exploring the frontiers of AI and machine learning. Today, I want to share with you a project that I've been working on: Awesome GPT Prompt Engineering. It's a curated list of resources, tools, and other shiny things for GPT prompt engineering.