---
license: apache-2.0
tags:
- stripedhyena
- long context
- deep signal processing
- hybrid
- biology
- genomics
- phage
- microviridae
---

# Evo 1 - Microviridae

<p align="center">
<img src="/static-proxy?url=https%3A%2F%2Fcdn-uploads.huggingface.co%2Fproduction%2Fuploads%2F62a1306bbe7fa896d2c8de44%2FJoEHcvLTUlHoMcgh3mmAz.png" width="70%" />
</p>

## About 

This is a fine-tuned version of Evo 1, a biological foundation model capable of long-context modeling and design, specifically adapted for Microviridae phage sequences.

Evo uses the [StripedHyena architecture](https://github.com/togethercomputer/stripedhyena) to enable modeling of sequences at a single-nucleotide, byte-level resolution with near-linear scaling of compute and memory relative to context length.

## Model Details

- **Base Model**: Evo 1 7B 131K base
- **Fine-tuning**: 5,000 steps on Microviridae bacteriophage genomes
- **Architecture**: StripedHyena
- **Context Length**: 131,072 tokens
- **Parameters**: 7B

## Usage

This model uses the StripedHyena architecture. For loading and generation, please refer to the [Evo repository](https://github.com/evo-design/evo).

```python
# Example usage with Evo framework
from evo import Evo

# Load base model and apply fine-tuned weights
model = Evo('evo-1-131k-base')
# Load the fine-tuned checkpoint
checkpoint = torch.load('pytorch_model.bin')
model.load_state_dict(checkpoint)
```

## Training

Fine-tuned from `evo-1-131k-base` on Microviridae phage sequences for 5,000 steps.

## License

Apache 2.0