From f2844d27eb99156e9967a813a75a1da78d18df10 Mon Sep 17 00:00:00 2001 From: AnastasiaPodrabinek Date: Wed, 28 Aug 2024 09:58:01 +0300 Subject: [PATCH] Update extract-models.en.mdx As the information extraction task doesn't allow any creativity around output, the best consistency is reached with temperature 0. The same should be applied to other task with expected deterministic behavior, for example classification --- pages/prompts/information-extraction/extract-models.en.mdx | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/pages/prompts/information-extraction/extract-models.en.mdx b/pages/prompts/information-extraction/extract-models.en.mdx index 7c99a9d7b..a56b0278d 100644 --- a/pages/prompts/information-extraction/extract-models.en.mdx +++ b/pages/prompts/information-extraction/extract-models.en.mdx @@ -39,7 +39,7 @@ Abstract: {input} "content": "Your task is to extract model names from machine learning paper abstracts. Your response is an array of the model names in the format [\\\"model_name\\\"]. If you don't find model names in the abstract or you are not sure, return [\\\"NA\\\"]\n\nAbstract: Large Language Models (LLMs), such as ChatGPT and GPT-4, have revolutionized natural language processing research and demonstrated potential in Artificial General Intelligence (AGI). However, the expensive training and deployment of LLMs present challenges to transparent and open academic research. To address these issues, this project open-sources the Chinese LLaMA and Alpaca…" } ], - temperature=1, + temperature=0, max_tokens=250, top_p=1, frequency_penalty=0, @@ -69,7 +69,7 @@ Abstract: {input} frequency_penalty=0, prompt_truncate_len=1024, context_length_exceeded_behavior="truncate", - temperature=0.9, + temperature=0, max_tokens=4000 ) ``` @@ -79,4 +79,4 @@ Abstract: {input} ## Reference -- [Prompt Engineering Guide](https://www.promptingguide.ai/introduction/examples#information-extraction) (16 March 2023) \ No newline at end of file +- [Prompt Engineering Guide](https://www.promptingguide.ai/introduction/examples#information-extraction) (16 March 2023)