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Worked-out example: Surprisal from a causal (GPT) model as a cognitive processing bottleneck in reading2 years ago
Data analysis | 0. Preprocessing | 1. Add surprisal values to the dataset | 2. Analyze the dataset with a Bayesian hierarchical model | Conclusion | References
pangoling 1.0.3Bruno Nicenboim example.Rmd
Using a GPT2 transformer model to get word predictability2 years ago
References
pangoling 1.0.3Bruno Nicenboim intro-gpt2.Rmd
Troubleshooting the use of Python in R2 years ago
Module not found error in Rstudio | HTTPSConnectionPool error
pangoling 1.0.3Bruno Nicenboim troubleshooting.Rmd
Using a Bert model to get the predictability of words in their context2 years ago
References
pangoling 1.0.3Bruno Nicenboim intro-bert.Rmd