---
license: apache-2.0
language:
- en
---

## StripedHyena-Hessian-7B (SH-7B)

### About 

One of the focus areas at Together Research is new architectures for long context, improved training, and inference performance over the Transformer architecture. Spinning out of a research program from our team and academic collaborators, with roots in signal processing-inspired sequence models, we are excited to introduce the StripedHyena models. StripedHyena is the first alternative model competitive with the best open-source Transformers of similar sizes in short and long-context evaluations.

- Read more here in [our blog](https://together-ai.webflow.io/blog/stripedhyena-7b)
- Play with the model on our playground!
- Dive into the details of our [Standalone implementation](https://github.com/togethercomputer/stripedhyena)

### Model Architecture

StripedHyena is a hybrid architecture composed of multi-head, grouped-query attention and gated convolutions arranged in [Hyena](https://arxiv.org/abs/2302.10866) blocks, different from traditional decoder-only Transformers.  
  - Costant memory decoding in Hyena blocks via representation of convolutions as state-space models (modal or canonical form), or as truncated filters.
  - Low latency, faster decoding and higher throughput than Transformers. 
  - Improvement to training and inference-optimal scaling laws, compared to Transformers.
  - Trained on sequences of up to 32k, allowing it to process longer prompts.