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Run the fill-mask pipeline and check the raw results.

Source: R/FMAT.R
fill_mask.Rd

Normal users should use FMAT_run(). This function is only for technical check.

Usage

fill_mask(query, model, targets = NULL, topn = 5, gpu)

fill_mask_check(query, models, targets = NULL, topn = 5, gpu)

Arguments

query

Query sentence with mask token.

model, models

Model name(s).

targets

Target words to fill in the mask. Defaults to NULL (return the top 5 most likely words).

topn

Number of the most likely predictions to return. Defaults to 5.

gpu

Use GPU (3x faster than CPU) to run the fill-mask pipeline? Defaults to missing value that will automatically use available GPU (if not available, then use CPU). An NVIDIA GPU device (e.g., GeForce RTX Series) is required to use GPU. See Guidance for GPU Acceleration.

Options passing to the device parameter in Python:

  • FALSE: CPU (device = -1).

  • TRUE: GPU (device = 0).

  • Any other value: passing to transformers.pipeline(device=...) which defines the device (e.g., "cpu", "cuda:0", or a GPU device id like 1) on which the pipeline will be allocated.

Value

A data.table of raw results.

Functions

  • fill_mask(): Check performance of one model.

  • fill_mask_check(): Check performance of multiple models.

Examples

if (FALSE) { # \dontrun{
query = "Paris is the [MASK] of France."
models = c("bert-base-uncased", "bert-base-cased")

d.check = fill_mask_check(query, models, topn=2)
} # }