inference-providers/pr_2713/en/tasks/summarization.md

Summarization

Summarization is the task of producing a shorter version of a document while preserving its important information. Some models can extract text from the original input, while other models can generate entirely new text.

For more details about the summarization task, check out its dedicated page! You will find examples and related materials.

Recommended models

• facebook/bart-large-cnn: A strong summarization model trained on English news articles. Excels at generating factual summaries.
• Falconsai/medical_summarization: A summarization model trained on medical articles.

Explore all available models and find the one that suits you best here, or from the terminal with the hf CLI:

hf models ls --warm --pipeline-tag summarization --sort trending_score

Using the API

<InferenceSnippet pipeline=summarization providersMapping={ {"hf-inference":{"modelId":"human-centered-summarization/financial-summarization-pegasus","providerModelId":"human-centered-summarization/financial-summarization-pegasus"}} } />

API specification

Request

Headers
authorization	string	Authentication header in the form 'Bearer: hf_****' when hf_**** is a personal user access token with "Inference Providers" permission. You can generate one from your settings page.

Payload
inputs*	string	The input text to summarize.
parameters	object
clean_up_tokenization_spaces	boolean	Whether to clean up the potential extra spaces in the text output.
truncation	enum	Possible values: do_not_truncate, longest_first, only_first, only_second.
generate_parameters	object	Additional parametrization of the text generation algorithm.

Response

| Body | | | :--- | :--- | :--- | | summary_text | string | The summarized text. |