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<title>Botanic1 | Genomic language models for land plants</title>
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<h1 id="intro-title">Genomic language models<br>for land plants.</h1>
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<a class="primary" href="https://huggingface.co/collections/living-models/botanic1-6a97f4e3c33f3d109a75057d" target="_blank" rel="noopener">Model cards <span aria-hidden="true">↗</span></a>
<a href="https://www.biorxiv.org/content/10.64898/2026.09.04.749355v2" target="_blank" rel="noopener">Technical report <span class="ext">bioRxiv</span></a>
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<nav class="landing-tabs" aria-label="About Botanic1">
<a id="tab-overview" href="#overview">Overview</a>
<a id="tab-use" href="#use">Use the model</a>
<a id="tab-models" href="#models">Models & data</a>
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<section class="landing-panel" id="overview" aria-labelledby="tab-overview">
<div class="facts">
<article class="fact">
<p class="fact-label">Model size</p>
<h2>318M to 3.2B parameters</h2>
<p>Botanic1-S scores 0.758 on the aggregate benchmark across nine task families. PlantCAD2-L scores 0.752, Carbon-8B 0.723, and Evo 2-7B 0.716.</p>
<figure class="overview-plot" id="overview-benchmark" aria-label="Model benchmark comparison" hidden></figure>
<p class="fact-note">Frozen models · aggregate test score (S<sub>bal</sub><sup>test</sup>) · whiskers are 95% CIs</p>
<a class="text-link" href="leaderboard.html">Scores by task and species <span aria-hidden="true">↗</span></a>
</article>
<article class="fact">
<p class="fact-label">Species coverage</p>
<h2>320 land plant species</h2>
<p>Pre-training spans bryophytes, vascular spore plants, gymnosperms, and flowering plants.</p>
<figure class="overview-plot" id="overview-corpus" aria-label="Training corpus by plant family" hidden></figure>
<a class="text-link" href="corpus.html">Explore the training species <span aria-hidden="true">↗</span></a>
</article>
<article class="fact">
<p class="fact-label">Zero-shot scoring</p>
<h2>Variant prioritisation</h2>
<p>Botanic1-XL recovers 49.9% of validated causal variants within the top 1% of candidates (~60 variants out of a median of 5,904 per locus), across 545 studies in 14 species, from the sequence and mutation allele alone.</p>
<figure class="overview-plot" id="overview-causal" aria-label="Causal-variant recall curves" hidden></figure>
<a class="text-link" href="causal-variants.html">Explore the variant benchmark <span aria-hidden="true">↗</span></a>
</article>
<article class="fact">
<p class="fact-label">Fine-tuning</p>
<h2>Molecular phenotype predictions</h2>
<p>Easier and better fine-tuning for promoter and terminator strength, poly(A) sites, lncRNA classification, chromatin accessibility, and TF-family binding.</p>
<figure class="overview-plot" id="overview-finetune" aria-label="Fine-tuning results across six experiments" hidden></figure>
<p class="fact-note">Full fine-tuning · LoRA · IA³</p>
<a class="text-link" href="https://www.biorxiv.org/content/10.64898/2026.09.04.749355v2" target="_blank" rel="noopener">Methods and results in the report <span aria-hidden="true">↗</span></a>
</article>
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<p class="panel-note">Evaluations, uncertainty estimates, and species-level results are detailed in the <a href="https://www.biorxiv.org/content/10.64898/2026.09.04.749355v2" target="_blank" rel="noopener">technical report</a>.</p>
<div class="section-intro" id="cite">
<h2>Cite</h2>
<p>Barozet A., Cabeli V., Ogier du Terrail J., Rukhovich A., Janssoone T., Klajer G., Sheikhitarghi Z., Andrews G., Veran C., Strouk L. <em>BOTANIC-1: a series of long-context plant genomic foundation models in the agentic era.</em> bioRxiv (2026). doi: <a href="https://doi.org/10.64898/2026.09.04.749355" target="_blank" rel="noopener">10.64898/2026.09.04.749355</a></p>
</div>
<div class="citation-box"><button type="button" class="copy-bibtex" aria-label="Copy BibTeX to clipboard">Copy BibTeX</button>
<pre class="citation"><code>@article{Barozet2026.09.04.749355,
author = {Barozet, Am{\'e}lie and Cabeli, Vincent and Ogier du Terrail, Jean
and Rukhovich, Alexey and Janssoone, Thomas and Klajer, Gary
and Sheikhitarghi, Zeinab and Andrews, Gregory and Veran, Cyril
and Strouk, L{\'e}onard},
title = {BOTANIC-1: a series of long-context plant genomic foundation
models in the agentic era},
journal = {bioRxiv},
year = {2026},
elocation-id = {2026.09.04.749355},
doi = {10.64898/2026.09.04.749355},
publisher = {Cold Spring Harbor Laboratory},
URL = {https://www.biorxiv.org/content/early/2026/09/09/2026.09.04.749355},
eprint = {https://www.biorxiv.org/content/early/2026/09/09/2026.09.04.749355.full.pdf},
}</code></pre></div>
</section>
<section class="landing-panel" id="use" aria-labelledby="tab-use">
<div class="section-intro">
<p>Model cards contain instructions and tutorials</p>
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<div class="workflow-list">
<article class="workflow">
<div><h3>Score variants</h3><p>Provide a reference sequence, a variant position, and an alternate base. Get a likelihood ratio for each substitution, with no task-specific training.</p></div>
<a class="text-link" href="https://huggingface.co/living-models/Botanic1-S#2-zero-shot-variant-effect-scoring-llr" target="_blank" rel="noopener">Variant-scoring example <span aria-hidden="true">↗</span></a>
</article>
<article class="workflow">
<div><h3>Extract embeddings</h3><p>Provide DNA sequences. Get a representation at each nucleotide to train a probe for your task.</p></div>
<a class="text-link" href="https://huggingface.co/living-models/Botanic1-S#1-generating-embeddings" target="_blank" rel="noopener">Embedding example <span aria-hidden="true">↗</span></a>
</article>
<article class="workflow">
<div><h3>Fine-tune on your data</h3><p>Use labelled sequences to adapt the model with full fine-tuning or parameter-efficient methods.</p></div>
<a class="text-link" href="https://huggingface.co/living-models/Botanic1-S#4-fine-tuning-lora-or-full" target="_blank" rel="noopener">Fine-tuning scripts <span aria-hidden="true">↗</span></a>
</article>
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</section>
<section class="landing-panel" id="models" aria-labelledby="tab-models">
<div class="section-intro">
<h2>Models, data, and report</h2>
</div>
<div class="resource-list">
<a href="https://huggingface.co/collections/living-models/botanic1-6a97f4e3c33f3d109a75057d" target="_blank" rel="noopener"><span>Model collection <span aria-hidden="true">↗</span></span><span class="small">Checkpoints, model cards, code examples, and licence.</span></a>
<a href="https://huggingface.co/datasets/living-models/Botanic1-pretraining" target="_blank" rel="noopener"><span>Pre-training corpus <span aria-hidden="true">↗</span></span><span class="small">Sequence windows from 320 species and source assemblies.</span></a>
<a href="https://huggingface.co/living-models/Botanic1-M-sae-k64-codebook8192" target="_blank" rel="noopener"><span>SAE model <span aria-hidden="true">↗</span></span><span class="small">Sparse autoencoder for Botanic1-M.</span></a>
<a href="https://www.biorxiv.org/content/10.64898/2026.09.04.749355v2" target="_blank" rel="noopener"><span>Technical report <span class="small">bioRxiv</span></span><span class="small">Training, evaluation, long context, and interpretability.</span></a>
</div>
<div class="section-intro" id="cite-models">
<h2>Cite</h2>
<p>Barozet A., Cabeli V., Ogier du Terrail J., Rukhovich A., Janssoone T., Klajer G., Sheikhitarghi Z., Andrews G., Veran C., Strouk L. <em>BOTANIC-1: a series of long-context plant genomic foundation models in the agentic era.</em> bioRxiv (2026). doi: <a href="https://doi.org/10.64898/2026.09.04.749355" target="_blank" rel="noopener">10.64898/2026.09.04.749355</a></p>
</div>
<div class="citation-box"><button type="button" class="copy-bibtex" aria-label="Copy BibTeX to clipboard">Copy BibTeX</button>
<pre class="citation"><code>@article{Barozet2026.09.04.749355,
author = {Barozet, Am{\'e}lie and Cabeli, Vincent and Ogier du Terrail, Jean
and Rukhovich, Alexey and Janssoone, Thomas and Klajer, Gary
and Sheikhitarghi, Zeinab and Andrews, Gregory and Veran, Cyril
and Strouk, L{\'e}onard},
title = {BOTANIC-1: a series of long-context plant genomic foundation
models in the agentic era},
journal = {bioRxiv},
year = {2026},
elocation-id = {2026.09.04.749355},
doi = {10.64898/2026.09.04.749355},
publisher = {Cold Spring Harbor Laboratory},
URL = {https://www.biorxiv.org/content/early/2026/09/09/2026.09.04.749355},
eprint = {https://www.biorxiv.org/content/early/2026/09/09/2026.09.04.749355.full.pdf},
}</code></pre></div>
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