Token Classification API Inference
Usage
hf_ez_token_classification_api_inference(
string,
aggregation_strategy = "simple",
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 classified
- aggregation_strategy
(Default: simple). There are several aggregation strategies.
none: Every token gets classified without further aggregation.
simple: Entities are grouped according to the default schema (B-, I- tags get merged when the tag is similar).
first: Same as the simple strategy except words cannot end up with different tags. Words will use the tag of the first token when there is ambiguity.
average: Same as the simple strategy except words cannot end up with different tags. Scores are averaged across tokens and then the maximum label is applied.
max: Same as the simple strategy except words cannot end up with different tags. Word entity will be the token with the maximum score.- 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).
- ...
Additional arguments passed internally, including the model object or model ID.