An automatic evaluation package for assessing the quality of LLM-generated multi-document topic sets.
Project description
Tpower5Score
An automatic evaluation package for assessing the quality of LLM-generated multi-document topic sets.
📦 How to install
pip install tpower5score
🚀 How to use
topics_set = [<topics_set>]
docs = [<documents>]
agg_weights = {
'Interpretability': 0.2,
'Topic Coverage': 0.2,
'Document Coverage': 0.2,
'Overlap': 0.2,
'Rank': 0.2
}
aspects, agg_score = tpower5score.evaluate(topics_set, docs)
Or see working example in examples/main.py
📖 Citation
If you use this package in your work, please cite:
@article{
title={$T^5Score$: A Methodology for Automatically Assessing the Quality of LLM Generated Multi-Document Topic Sets},
author={Trainin Itamar, Omri Abend},
}
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
tpower5score-0.1.1.tar.gz
(7.2 kB
view details)
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file tpower5score-0.1.1.tar.gz.
File metadata
- Download URL: tpower5score-0.1.1.tar.gz
- Upload date:
- Size: 7.2 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.11.2
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
148cb0561f5fc490abf7d720aba83aaaefcab49990cae50c0b6af9bb025f58c3
|
|
| MD5 |
239f644657d0ea877ae232bdd5eb0823
|
|
| BLAKE2b-256 |
033f7defe8b6f3f1cdd9b051f70291daeb9133a673b61e4e1b849865e2426386
|
File details
Details for the file tpower5score-0.1.1-py3-none-any.whl.
File metadata
- Download URL: tpower5score-0.1.1-py3-none-any.whl
- Upload date:
- Size: 7.5 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.11.2
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
72b02e54a930223ff037b193088bd8d30c175f3676d48ffc0f62429e675ab370
|
|
| MD5 |
3e8d583f3e382c1188caf1e4f95f7a91
|
|
| BLAKE2b-256 |
ec4a28aafc72a65305ecfe7b2d41d87d9c46a03e2712bedec4d0c24d215c3f89
|