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.
Explore all available models and find the one that suits you best here.
There are currently no snippet examples for the summarization task, as no providers support it yet.
| 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. |
| Body | ||
|---|---|---|
| summary_text | string | The summarized text. |