pangoling
1.0.3Access to Large Language Model Predictions
Overview
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).
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Health
- OK2026-06-0812 OK · 0 NOTE · 0 WARNING · 0 ERROR · 1 FAILURE
- WARNING2026-06-0712 OK · 0 NOTE · 1 WARNING · 0 ERROR · 0 FAILURE
- OK2026-04-0914 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- ERROR2026-03-2513 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
- OK2026-03-1014 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Documentation
- Examples that run
- 95%
- Documented parameters
- 99%
- Return-value docs
- 100%
- References docs
- 0%
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Code & Tests
People & History
1 release. R releases are shown for context.
- RR 4.6.0 released · 2026-04-24
- 1.0.3Latest2026-03-10 · current release
- RR 4.5.0 released · 2025-04-11
Package metadata
- First published
- 2025-04-07
- Total releases
- 1 / 1 yrs
- License
- MIT + file LICENSE OSI
- Minimum R
- ≥ 4.1.0
- Bundled data
- 19 KB / 2 files
- Download size
- 1.4 MB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet