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vector-institute/pmc-helper-models
pmc-helper-models is a machine learning model from vector-institute. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
These checkpoints contain helper models used in creating the PMC-2M dataset.
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Updated Feb 17, 2025
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From the Hugging Face model README
These checkpoints contain helper models used in creating the PMC-2M dataset.
Make sure to run this script before using the pipeline.
from huggingface_hub import snapshot_download
weights_dir = snapshot_download(
repo_id="vector-institute/pmc-helper-models",
local_dir="openpmcvl/granular/checkpoints",
allow_patterns=["*.pt", "*.pth"]
)
The weights will be downloaded to the specified local_dir. Your existing code can then load them from this location.
Change the local_dir to the path of the directory leading to openpmcvl/granular/checkpoints in your project.
TBD
The original weights come from PMC-CLIP paper. Please cite them if using the weights.
@misc{lin2023pmcclipcontrastivelanguageimagepretraining,
title={PMC-CLIP: Contrastive Language-Image Pre-training using Biomedical Documents},
author={Weixiong Lin and Ziheng Zhao and Xiaoman Zhang and Chaoyi Wu and Ya Zhang and Yanfeng Wang and Weidi Xie},
year={2023},
eprint={2303.07240},
archivePrefix={arXiv},
primaryClass={cs.CV},
url={https://arxiv.org/abs/2303.07240},
}