Returns the configuration of a masked model.
Usage
masked_config(
model = getOption("pangoling.masked.default"),
config_model = NULL
)
Arguments
- model
Name of a pre-trained model or folder.
- config_model
List with other arguments that control how the model from Hugging Face is accessed.
Details
A masked language model (also called BERT-like, or encoder model) is a type of large language model that can be used to predict the content of a mask in a sentence.
If not specified, the masked model that will be used is the one set in
specified in the global option pangoling.masked.default
, this can be
accessed via getOption("pangoling.masked.default")
(by default
"bert-base-uncased"). To change the default option
use options(pangoling.masked.default = "newmaskedmodel")
.
A list of possible masked can be found in Hugging Face website.
Using the config_model
and config_tokenizer
arguments, it's possible to
control how the model and tokenizer from Hugging Face is accessed, see the
python method
from_pretrained
for details. In case of errors
check the status of
https://status.huggingface.co/
See also
Other masked model functions:
masked_lp()
,
masked_preload()
,
masked_tokens_tbl()