hf_summarization_payload: Summarization Task Payload

In farach/huggingfaceR: Hugging Face State-of-the-Art Models in R

Summarization Task Payload

Description

This task is well known to summarize longer text into shorter text. Be careful, some models have a maximum length of input. That means that the summary cannot handle full books for instance.

Usage

hf_summarization_payload(
  string,
  min_length = NULL,
  max_length = NULL,
  top_k = NULL,
  top_p = NULL,
  temperature = 1,
  repetition_penalty = NULL,
  max_time = NULL
)

Arguments

string	a string to be summarized
min_length	Integer to define the minimum length in tokens of the output summary. Default: NULL
max_length	Integer to define the maximum length in tokens of the output summary. Default: NULL
top_k	Integer to define the top tokens considered within the sample operation to create new text. Default: NULL
top_p	Float to define the tokens that are within the sample operation of text generation. Add tokens in the sample for more probable to least probable until the sum of the probabilities is greater than top_p. Default: NULL
temperature	Float (0.0-100.0). The temperature of the sampling operation. 1 means regular sampling, 0 means always take the highest score, 100.0 is getting closer to uniform probability. Default: 1.0
repetition_penalty	Float (0.0-100.0). The more a token is used within generation the more it is penalized to not be picked in successive generation passes. Default: NULL
max_time	Float (0-120.0). The amount of time in seconds that the query should take maximum. Network can cause some overhead so it will be a soft limit. Default: NULL

Value

An inference payload

See Also

https://huggingface.co/docs/api-inference/detailed_parameters#summarization-task

farach/huggingfaceR documentation built on Feb. 4, 2023, 10:31 p.m.