Prompt engineering is a process used in AI where one or several tasks are converted to a prompt-based dataset that a language model is then trained to learn. Like most processes, the quality of the inputs determines the quality of the outputs.
Designing effective prompts increases the likelihood that the model will return a response that is both favorable and contextual. Prompt engineering is a process used in AI where one or several tasks are converted to a prompt-based dataset that a language model is then trained to learn. The purpose of prompt engineering is to design prompts that will elicit a desired response from a language model.
GPT-3 is a large language model created by OpenAI. It is trained on 175 billion parameters and is trying to emulate human natural language. Now that you know a bit about GPT-3, let’s take a look at how you can…
If you’re looking to fine-tune a GPT-3 large language model, this article will give you a step-by-step guide on how to do just that. Fine-tuning can help to reduce the amount of data required to train a model and can…
In this article we are looking at 5 practical tips for everyday prompt engineering use cases with GPT-3 or other similar LLM. I think these 5 tips could save you a lot of time in just simple everyday tasks. Read…
In this article we are looking at 5 beginner tips for prompt engineering with GPT-3. I think these 5 tips have a lot of practical use cases. There are more advanced ways to use a large language model, but it…
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