changed the wording of moral scenarios

stripping the whitespace from the input so that the filtering works with or without whitespace

Support for multi column filtering using comma seperated values (#2)

Updated

Updated description and data

updated

Completed loaded form csv

loading from csv instead of processing data each time

updated

WIP. Loading data from csv

Changed error logging from print statements to logger. It is not currently working to save to a file locally

Catching exceptions in processing files. As new data is introduced, I want to know which files may have different formats and cause problems, but the application shouldn't halt if it can't process a single file

Added new results from hugging face evaluations

added code to split moral scenario question from one question to two

updated gitignore

updated dev requirements

Extracted plotting functions from moral_app to plotting_utils to improve organization and testability

copied main streamlit application to one that will specifically investigate moral reasoning

updated date and model count

updated results

Added new hugging face results

added a test and removed the code to only test a specific file because that code did not work

updated to run submodule update

Update pytest run to only run specific test files. Other test files are not ready to be run on a different system yet

Merge branch 'main' of https://github.com/c1505/LLM-Dashboard into main

Added additional results

Updated to reflect number of models. Previously, I think there were duplicates

Create python-app.yml

Updated dependencies

Show a random question from the moral scenarios evaluation

Returning just a single file per model directory. Manually removing gpt-j-6b for now because there is something that is causing problems with processing the data

added new results

TEMPORARY. deleted gpt-j-6b from subdirectory until problems are fixed

updated results

updated dev requirements

added dev requirmenents

Updated model count

Updated contaminated models

Added statement of removal of models

removed commented code

updated update data

removing models that are known to have training data contaminated with evaluations

updated with new hugging face results

updated pipeline and init

removed commented code

added a test

shortened file name

shortened file name

using URL as file name

WIP. Updated download file. Can now download all files. Need to integrate that code to loop through all files to download or combine files first into a single dataframe and then save that