Summarization API Inference
Usage
hf_ez_summarization_api_inference(
string,
min_length = NULL,
max_length = NULL,
top_k = NULL,
top_p = NULL,
temperature = 1,
repetition_penalty = NULL,
max_time = NULL,
tidy = TRUE,
use_gpu = FALSE,
use_cache = FALSE,
wait_for_model = FALSE,
use_auth_token = NULL,
stop_on_error = FALSE,
...
)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
- tidy
Whether to tidy the results into a tibble. Default: TRUE (tidy the results)
- use_gpu
Whether to use GPU for inference.
- use_cache
Whether to use cached inference results for previously seen inputs.
- wait_for_model
Whether to wait for the model to be ready instead of receiving a 503 error after a certain amount of time.
- use_auth_token
The token to use as HTTP bearer authorization for the Inference API. Defaults to HUGGING_FACE_HUB_TOKEN environment variable.
- stop_on_error
Whether to throw an error if an API error is encountered. Defaults to FALSE (do not throw error).