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updated links on webpage
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zahid-isu committed Oct 30, 2024
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Expand Up @@ -234,15 +234,15 @@ <h1 class="title is-1 publication-title"> BioTrove: A Large Curated Image Datase
</span>
<!-- Hugging Face link -->
<span class="link-block">
<a href="https://huggingface.co/datasets/ChihHsuan-Yang/Arboretum" target="_blank" class="external-link button is-normal is-rounded is-dark">
<a href="https://huggingface.co/datasets/BGLab/BioTrove" target="_blank" class="external-link button is-normal is-rounded is-dark">
<span class="icon">
&#129303;
</span>
<span>Dataset card</span>
</a>
</span>
<span class="link-block">
<a href="https://huggingface.co/ChihHsuan-Yang/ArborCLIP" target="_blank" class="external-link button is-normal is-rounded is-dark">
<a href="https://huggingface.co/BGLab/BioTrove-CLIP" target="_blank" class="external-link button is-normal is-rounded is-dark">
<span class="icon">
&#129303;
</span>
Expand Down Expand Up @@ -388,31 +388,6 @@ <h2 class="title is-3">Dataset Features</h2>
</div>
</section>

<!-- dataprep -->
<section class="hero is-small" style="margin-bottom: 1rem;">
<div class="hero-body" style="padding-bottom: 1rem;">
<div class="container">
<h2 class="title is-3">Data Preparation</h2>
<div class="content">
<p>
Our <a href="https://github.com/baskargroup/BioTrove/blob/main/Arbor-preprocess/README_arbor_process.md" target="_blank" class="underline-link">Github</a> includes the pipeline and <a href="https://pypi.org/project/arbor-process/" target="_blank" class="underline-link">arbor-process</a> package installation instructions for the data preparation.
The metadata can be downloaded from <a href="https://huggingface.co/datasets/ChihHsuan-Yang/Arboretum" target="_blank" class="underline-link">HF</a>. This procedure will generate machine learning-ready image-text pairs from the downloaded metadata in four steps:
</p>
</div>
<div class="image-container" style="text-align: center;">
<img src="static/images/dataprep.png" alt="datprep" style="width: 80%; height: auto;">
</div>
</div>
</div>
</section>

<style>
.underline-link {
text-decoration: underline;
}
</style>
<!-- end of dataprep -->


<!-- Main Datasets Section -->
<section class="hero is-medium" style="margin-bottom: 1rem;">
Expand Down Expand Up @@ -471,6 +446,31 @@ <h2 class="title is-4">New Benchmark</h3>
</div>
</section>

<!-- dataprep -->
<section class="hero is-small" style="margin-bottom: 1rem;">
<div class="hero-body" style="padding-bottom: 1rem;">
<div class="container">
<h2 class="title is-3">Data Preparation</h2>
<div class="content">
<p>
Our <a href="https://github.com/baskargroup/BioTrove/blob/main/Arbor-preprocess/README_arbor_process.md" target="_blank" class="underline-link">Github</a> includes the pipeline and <a href="https://pypi.org/project/arbor-process/" target="_blank" class="underline-link">arbor-process</a> package installation instructions for the data preparation.
The metadata can be downloaded from <a href="https://huggingface.co/datasets/BGLab/BioTrove-Train" target="_blank" class="underline-link">HF</a>. This procedure will generate machine learning-ready image-text pairs from the downloaded metadata in four steps:
</p>
</div>
<div class="image-container" style="text-align: center;">
<img src="static/images/dataprep.png" alt="datprep" style="width: 80%; height: auto;">
</div>
</div>
</div>
</section>

<style>
.underline-link {
text-decoration: underline;
}
</style>
<!-- end of dataprep -->

<!-- ArborCLIP model -->
<section class="hero is-small">
<div class="hero-body">
Expand Down Expand Up @@ -508,9 +508,9 @@ <h2 class="title is-3">ARBORCLIP Model</h2>
<h1 class="title is-4">Model Weights</h1>
<div class="content">
<p>
The <b>ARBORCLIP</b> models were developed for the benefit of the AI community as an open-source product.
We released three <b>ARBORCLIP</b> trained models based on OpenAI's <a href="https://openai.com/index/clip/" target="_blank" class="underline-link">CLIP</a> model.
The models were trained on <b>ARBORETUM-Train</b> dataset. Please utilize our HuggingFace <a href="https://huggingface.co/ChihHsuan-Yang/ArborCLIP" target="_blank" class="underline-link">Model card</a> to access the model checkpoints.
The <b>BioTrove-CLIP</b> models were developed for the benefit of the AI community as an open-source product.
We released three <b>BioTrove-CLIP</b> trained models based on OpenAI's <a href="https://openai.com/index/clip/" target="_blank" class="underline-link">CLIP</a> model.
The models were trained on <b>BioTrove-Train</b> dataset. Please utilize our HuggingFace <a href="https://huggingface.co/BGLab/BioTrove-CLIP" target="_blank" class="underline-link">Model card</a> to access the model checkpoints.
</p>
</div>
</div>
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