gbrixi/evo2_7b_microviridae_vllm

Evo 2 - Microviridae (vLLM)

Evo 2 is a state of the art DNA language model for long context modeling and design. Evo 2 models DNA sequences at single-nucleotide resolution at up to 1 million base pair context length using the StripedHyena 2 architecture, using Savanna. Evo 2 was trained autoregressively on OpenGenome2, a dataset containing 8.8 trillion tokens from all domains of life.

Evo 2 7B Microviridae is a fine-tuned version of Evo 2 7B base trained on Microviridae genomes.

This is the vLLM checkpoint of evo-design/evo-2-7b-8k-microviridae: the same model, converted to safetensors for the vLLM backend of Evo 2. Load it with

from evo2 import Evo2

model = Evo2('evo2_7b_microviridae', backend='vllm')

For the Vortex backend, use evo-design/evo-2-7b-8k-microviridae.

Usage

For usage instructions, please refer to the Evo 2 GitHub repository.

Model Details

This model was fine-tuned from the Evo 2 7B base model on a curated dataset of Microviridae genomes.

• Base Model: Evo 2 7B base
• Context Length: 10,240 tokens
• Checkpoint: 12,000 iterations

Evo 2 vLLM checkpoints

Evo 2 20B and 7B vLLM checkpoints, trained up to 1 million sequence length, are available here:

Checkpoint name	Num layers	Num parameters
evo2_20b	50	20B
evo2_7b	32	7B

We also share 7B and 1B base vLLM checkpoints trained on 8192 context length:

Checkpoint name	Num layers	Num parameters
evo2_7b_base	32	7B
evo2_1b_base	25	1B

Also available: evo2_7b_262k (7B, 262,144-token context) and evo2_7b_microviridae (7B base fine-tuned on Microviridae genomes).