gbrixi/evo2_7b_262k_vllm

Evo 2 7B 262k Context (vLLM)

This is an intermediate version of Evo 2 7B, trained with up to a 262,144 token context length.

Evo 2 is a state-of-the-art DNA language model trained autoregressively on trillions of DNA tokens.

For instructions, details, and examples, please refer to the GitHub and paper.

This is the vLLM checkpoint of arcinstitute/evo2_7b_262k: the same model, converted to safetensors for the vLLM backend of Evo 2. Load it with

from evo2 import Evo2

model = Evo2('evo2_7b_262k', backend='vllm')

For the Vortex backend, use arcinstitute/evo2_7b_262k.

Model Details

• Base Model: Evo 2 7B
• Context Length: 262,144 tokens (262k)
• Parameters: 7B
• Checkpoint: Iteration 12,500
• Architecture: 32 layers

Main Evo 2 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).

Usage

Please refer to the Evo 2 GitHub repository for detailed usage instructions and examples.