Немецкие овчарки Казахстана

[ShoponFFGS]

Often the result will be better if you provide more context, such as examples of how you do it today and what it is that you are not achieving optimally, as well as perhaps some details such as the industry you are in and what the goal is to improve this particular thing. Remember the language What is your best friend when communicating with a language model? Yes, precisely – language! With well worded prompts, you can help the model understand the intent behind the question and produce relevant and informative answers.

Here's a simple language checklist to keep in mind before you start typing prompts Clarifying instructions Including specific details and clarifying context in the prompt minimizes the risk of misunderstandings. Never assume that a model knows what you're talking about. Guiding Questions Include questions that [url=https://www.latestdatabase.com/brazil-whatsapp-number-list/]Brazil WhatsApp Number List[/url] guide the model to generate desired responses or follow a particular line of thought. Think about sentence structure Can your question be misunderstood? Be as specific and clear as possible. Avoid "negation" Language models do not always respond equally well to instructions involving "don't" or "avoid".

[url=https://www.latestdatabase.com/brazil-whatsapp-number-list/][img]https://btocdatabase.com/wp-content/uploads/2023/07/Brazil-WhatsApp-Number-List-300x300.jpg[/img][/url]

Instead, try to explain what it should do instead of what it should not do. Having said that Sometimes it is also useful to clarify what will be an undesirable result. English often works best Often a good tip can be to write prompts in English, and possibly ask the model to translate the output back into Norwegian. That's because most language models are based on English training data and are therefore better suited to understanding the nuances of the English language. . Try, fail – and try again! In working life, it is rare that everything fits on the first try. You often arrive at the best possible result when you test, experiment and adjust along the way. This is also the case with prompt engineering.