Merge pull request #238831 from mrbullwinkle/mrb_05_22_2023_reference_doc_update

[Azure OpenAI] Reference docs update

Author: prmerger-automator[bot]

articles/cognitive-services/openai/reference.md

@@ -62,7 +62,7 @@ POST https://{your-resource-name}.openai.azure.com/openai/deployments/{deploymen
 
 | Parameter | Type | Required? | Default | Description |
 |--|--|--|--|--|
-| ```prompt``` | string or array | Optional | ```<\|endoftext\|>``` | The prompt(s) to generate completions for, encoded as a string, a list of strings, or a list of token lists. Note that ```<\|endoftext\|>``` is the document separator that the model sees during training, so if a prompt isn't specified the model will generate as if from the beginning of a new document. |
+| ```prompt``` | string or array | Optional | ```<\|endoftext\|>``` | The prompt(s) to generate completions for, encoded as a string, or array of strings. Note that ```<\|endoftext\|>``` is the document separator that the model sees during training, so if a prompt isn't specified the model will generate as if from the beginning of a new document. |
 | ```max_tokens``` | integer | Optional | 16 | The maximum number of tokens to generate in the completion. The token count of your prompt plus max_tokens can't exceed the model's context length. Most models have a context length of 2048 tokens (except for the newest models, which support 4096). |
 | ```temperature``` | number | Optional | 1 | What sampling temperature to use, between 0 and 2. Higher values means the model will take more risks. Try 0.9 for more creative applications, and 0 (`argmax sampling`) for ones with a well-defined answer. We generally recommend altering this or top_p but not both. |
 | ```top_p``` | number | Optional | 1 | An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the top 10% probability mass are considered. We generally recommend altering this or temperature but not both. |