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README.md
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## Model Summary
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**Carbon-3B** is a 3B-parameter decoder-only autoregressive genomic foundation model trained on DNA and RNA sequences, with a primary focus on eukaryotes. It has a native context length of **32,768 6-mer tokens (≈ 197k DNA base pairs)** and extends to **65,536 tokens (≈ 393 kbp)** at inference time via YaRN. Carbon-3B is designed to be both strong and efficient: on generative tasks (sequence recovery), variant-effect prediction, and motif-perturbation discrimination, it matches the capability of substantially larger single-nucleotide baselines such as Evo2-7B while running several times faster.
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Carbon-3B is the **flagship** model of the Carbon family. We also release [**Carbon-8B**](https://huggingface.co/HuggingFaceBio/) for users who need additional capability at higher inference cost, and [**Carbon-500M**](https://huggingface.co/HuggingFaceBio/) — a small generative model intended for speculative decoding alongside Carbon-3B (or Carbon-8B).
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## Model Summary
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<p align="center">
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<img src="figures/pareto.png" alt="Pareto plot" width="800">
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</p>
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**Carbon-3B** is a 3B-parameter decoder-only autoregressive genomic foundation model trained on DNA and RNA sequences, with a primary focus on eukaryotes. It has a native context length of **32,768 6-mer tokens (≈ 197k DNA base pairs)** and extends to **65,536 tokens (≈ 393 kbp)** at inference time via YaRN. Carbon-3B is designed to be both strong and efficient: on generative tasks (sequence recovery), variant-effect prediction, and motif-perturbation discrimination, it matches the capability of substantially larger single-nucleotide baselines such as Evo2-7B while running several times faster.
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Carbon-3B is the **flagship** model of the Carbon family. We also release [**Carbon-8B**](https://huggingface.co/HuggingFaceBio/) for users who need additional capability at higher inference cost, and [**Carbon-500M**](https://huggingface.co/HuggingFaceBio/) — a small generative model intended for speculative decoding alongside Carbon-3B (or Carbon-8B).
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