pangoling-package {pangoling}R Documentation

pangoling: Access to Large Language Model Predictions

Description

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Provides access to word predictability estimates using large language models (LLMs) based on 'transformer' architectures via integration with the 'Hugging Face' ecosystem https://huggingface.co/. The package interfaces with pre-trained neural networks and supports both causal/auto-regressive LLMs (e.g., 'GPT-2') and masked/bidirectional LLMs (e.g., 'BERT') to compute the probability of words, phrases, or tokens given their linguistic context. For details on GPT-2 and causal models, see Radford et al. (2019) https://storage.prod.researchhub.com/uploads/papers/2020/06/01/language-models.pdf, for details on BERT and masked models, see Devlin et al. (2019) doi:10.48550/arXiv.1810.04805. By enabling a straightforward estimation of word predictability, the package facilitates research in psycholinguistics, computational linguistics, and natural language processing (NLP).

Details

These options are used to control various aspects of the pangoling package. Users can customize these options via the options() function by specifying ⁠pangoling.<option>⁠ names.

Use ⁠options(pangoling.<option> = <value>)⁠ to set these options in your session.

Author(s)

Maintainer: Bruno Nicenboim b.nicenboim@tilburguniversity.edu (ORCID)

Other contributors:

See Also

Useful links:

Examples

options(pangoling.verbose = FALSE) # Removes messages
options(pangoling.verbose = TRUE) # Show messages 

[Package pangoling version 1.0.3 Index]