ArcInstitute/evo2

Health v2 · maintenance only

Adoption not part of the score

4157 stars · 548 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

Evo 2 is a DNA foundation language model (1B-40B parameters) that models genomes at single-nucleotide resolution with up to 1 million base pair context length, built on the StripedHyena 2 architecture. This repository provides inference, embedding, and generation code, plus training and finetuning support, for running Evo 2 locally or via Nvidia NIM.

Use cases

• generate novel DNA sequences with a genome language model
• get embeddings for genomic sequences for downstream prediction
• predict variant effects from DNA sequences
• finetune a DNA foundation model on custom genomic data
• model long genomic contexts up to 1 million base pairs
• run a biological sequence model on GPU locally

When to choose

• you need a state-of-the-art DNA/genome language model for inference or finetuning
• you work in genomics and want long-context sequence modeling at nucleotide resolution
• you have NVIDIA GPUs (Hopper for large models) and want local genome generation or embeddings

When to avoid

• you need protein or RNA modeling rather than DNA
• you have no CUDA-capable NVIDIA GPU (large models require FP8 on Hopper)
• you want a lightweight CPU-only bioinformatics tool

Facets

library · maturity active

machine-learning deep-learning llm-inference llm-training sdk bioinformatics machine-learning deep-learning large-language-models python dna-language-model genomics genome-design long-context stripedhyena foundation-model inference linux gpu docker

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markdown · JSON · MCP: product_card(name="ArcInstitute/evo2")