
About the Summarization Models in Generative AI

About the Summarization Models in Generative AI
A version of the cohere.command pretrained model is available in OCI
Generative AI for text summarization. The summarization model is
 the same as one of the pretrained text generation models, but it has parameters that you can
 specify for text summarization. Use the summarization model for any text that you want to see a
 summary of. Input text and get important information out of that text.
 Important The summarization feature will be removed from the OCI
Generative AI playground, API, and CLI when the
 cohere.command v15.6 model is retired. Instead of this model, you can
 summarize text by using the chat models. For retirement dates see Retiring the Models.
The following categories are ideal text sources for summarization:
News articles
Blog posts
Chat transcripts
Scientific articles
Meeting notes
Product reviews
Summarization Model Parameters
When using the summarization model in the playground, you can get a different output by
 changing the following parameters.
Length
The approximate length of the summary. You can choose short, medium, or long. Short
 summaries are roughly up to two sentences long, medium summaries are between three and
 five sentences, and long summaries might have six or more sentences. For the
 Auto value, the model chooses a length based on the input
 size.
Format
Whether to display the summary in a free-form paragraph or in bullet points. For the
 Auto value, the model chooses the best format based on the
 input text.
Extractiveness
How much to reuse the input in the summary. Summaries with high extractiveness tend to
 use sentences verbatim, and summaries with low extractiveness tend to paraphrase.
Temperature
The level of randomness used to generate the output text.
 Tip To summarize a text, start with the temperature set to 0. If you don't
 require random results, we recommend a temperature value of 0.2. Use a higher value if,
 for example, you plan to select various summaries afterward. However, don't use a high
 temperature for summarization because a high temperature encourages the model to produce
 creative text, which might also include hallucinations and factually incorrect
 information.
Additional command
Other summarizing options such as style or focus. Write one or more additional commands
 in a natural language as instructions to the model, for example, "focus on dates", or
 "write in a conversational style", or "end the resume with END SUMMARY".
