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hulat-group/alignscore-base-checkpoint
alignscore-base-checkpoint is a machine learning model from hulat-group. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as mit.
This repository provides the AlignScore checkpoints required to run AlignScore-based evaluation within HULAT's NLP evaluation pipelines.
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Updated May 14, 2026
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From the Hugging Face model README
This repository provides the AlignScore checkpoints required to run AlignScore-based evaluation within HULAT's NLP evaluation pipelines.
AlignScore is an automatic evaluation metric designed to assess the alignment between a source text and a generated text, supporting tasks such as factual consistency evaluation, semantic preservation, summarization evaluation, and text simplification evaluation.
This repository currently includes:
AlignScore-base.ckptAlignScore-large.ckptThese files are intended to be used as pretrained checkpoints for AlignScore, especially in evaluation workflows involving generated or simplified texts.
| File | Description |
|---|---|
AlignScore-base.ckpt | Base AlignScore checkpoint |
AlignScore-large.ckpt | Large AlignScore checkpoint |
.gitattributes | Git LFS configuration |
README.md | Repository documentation |
Important: These files are checkpoints for the AlignScore metric. They are not standalone text generation models.
These checkpoints are intended for research and evaluation purposes, particularly for:
Within HULAT, these checkpoints are used as part of broader evaluation workflows for text simplification and accessibility-oriented NLP research.
For the English version of AlignScore, the checkpoint must be downloaded manually from this repository and placed in the expected local path.
Manual download:
https://huggingface.co/hulat-group/alignscore-base-checkpoint/tree/main
These checkpoints should be loaded through an AlignScore implementation or a compatible evaluation pipeline.
from alignscore import AlignScore
scorer = AlignScore(
model="roberta-base",
batch_size=16,
device="cuda:0",
ckpt_path="AlignScore_v2_es/checkpoint/checkpoints/AlignScore-base.ckpt"
)
score = scorer.score(
contexts=["The original source text goes here."],
claims=["The generated or simplified text goes here."]
)
print(score)