evo2-genome-model

name	evo2-genome-model
description	Operate Arc Institute Evo 2 for long-context DNA sequence scoring, zero-shot variant effect analysis, genomic embeddings, sequence generation, and model deployment. Use when a task explicitly needs Evo 2, million-base genomic context, DNA likelihood comparisons, genomic foundation-model embeddings, or generated DNA candidates across species.

Evo 2 Genome Model

Use Evo 2 as a genomic foundation model, not as a substitute for experimental or clinical validation.

Workflow

1. Define the task before choosing a checkpoint:
   • score reference and alternate sequences for zero-shot variant effects;
   • extract embeddings for a downstream classifier or retrieval system;
   • generate sequence continuations or design candidates;
   • fine-tune on a documented task-specific dataset.
2. Record the reference assembly, strand, coordinate convention, species, sequence length, and any ambiguous bases.
3. Choose the smallest suitable deployment:
   • use a 7B checkpoint for routine local scoring or generation on supported GPUs;
   • use 20B or 40B only when the expected gain justifies Hopper-class FP8 hardware;
   • use NVIDIA hosted API or NIM when local hardware is unsuitable.
4. Keep reference and alternate alleles in identical sequence context. Normalize variants before scoring and test reverse-complement sensitivity when strand orientation is not biologically fixed.
5. For embeddings, compare candidate intermediate layers on a held-out validation set instead of assuming the final layer is optimal.
6. For generation, preserve prompts, model identifier, temperature, top-k, random seed, and every post-generation filter.
7. Validate outputs with task-relevant baselines, external annotations, and wet-lab evidence where decisions are consequential.

Quality Controls

• Pin the checkpoint and package version; do not rely on a moving default.
• Run the upstream generation test after installation or hardware changes.
• Exclude sequence leakage between train, validation, and test splits.
• Report uncertainty from replicate prompts, seeds, or sequence windows.
• Screen generated DNA for biosafety, synthesis constraints, off-target homology, and unintended coding potential before any experimental use.
• Label zero-shot scores as model-derived evidence, not pathogenicity classifications.

Output Contract

Return:

• model and access path;
• input sequence provenance and preprocessing;
• scoring, embedding, or generation parameters;
• quality-control results and failed samples;
• limitations and the next orthogonal validation step.

Read references/operations.md for setup, checkpoint selection, examples, and canonical sources.