Evaluate language models using multiple choice items
Project description
LM Pub Quiz
Evaluate language models using multiple choice items
This library implements a knoweledge probing approach which uses LM's inherent ability to estimate the log-likelihood of any given textual statement. For more information visit the LM Pub Quiz website.
See also
Getting started
This short guide should get you started. For more detailed information visit the documentation.
Installing the Package
You can install the package via pip:
pip install lm-pub-quiz
or clone the repository and install the package using the -e
flag to make changes to the source code:
pip install -e lm-pub-quiz # Modify the path to the repository if necessary
For alternatives methods of installing the package, visit the documentation.
Example Usage
from lm_pub_quiz import Dataset, Evaluator
dataset_path = "<BEAR data path, e.g. ./transformer-knowledge-probe/data/BEAR>"
result_save_path = "<BEAR results save path>"
model_name = "gpt2"
# Load the BEAR dataset from its specific location
dataset = Dataset.from_path(dataset_path)
# Run the BEAR evaluator and save the results
evaluator = Evaluator.from_model(model_name, model_type="CLM", device="cuda")
results = evaluator.evaluate_dataset(dataset, save_path=result_save_path, batch_size=32)
Contributing
We welcome any questions, comments, or event PRs to this project to improve the package.
We use hatch to manage this project.
To run the test cases, run hatch run test
or hatch run all:test
(to test on multiple python versions).
In order to check the formatting and correct typing, run hatch run lint:all
.
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