|
--- |
|
license: apache-2.0 |
|
language: |
|
- en |
|
--- |
|
|
|
## StripedHyena-Nous-7B (SH-N 7B) |
|
|
|
<p align="center"> |
|
<img src="https://cdn-uploads.huggingface.co/production/uploads/62a1306bbe7fa896d2c8de44/Bfjh77emDsWOY-VmfvU9C.png" width="60%" /> |
|
</p> |
|
|
|
### 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. |
|
|
|
**StripedHyena-Nous-7B (SH-N 7B)** is our **chat model** for this release, and was developed with our collaborators at [Nous Research](https://nousresearch.com/). |
|
|
|
- Read more here in [our blog](https://www.together.ai/blog/stripedhyena-7b). |
|
- Play with the model on our [playground](https://api.together.xyz/playground/chat/togethercomputer/StripedHyena-Nous-7B)! |
|
- Dive into the details of our [standalone implementation](https://github.com/togethercomputer/stripedhyena), and our related research: [1](https://arxiv.org/abs/2302.10866), [2](https://arxiv.org/abs/2310.18780), [3](https://arxiv.org/abs/2311.05908). |
|
|
|
### 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 optimized Transformer architectures such as Llama-2. |
|
- Trained on sequences of up to 32k, allowing it to process longer prompts. |
|
|
|
### Prompt Format |
|
|
|
StripedHyena-Nous 7B uses this prompt format: |
|
|
|
``` |
|
### Instruction:\n{prompt}\n\n### Response:\n{response} |
|
``` |
|
|
|
### Disclaimer |
|
|
|
To use StripedHyena outside of the playground, you will need to install custom kernels. Please follow the instructions from the [standalone repository](https://github.com/togethercomputer/stripedhyena). |
|
|
|
StripedHyena is a mixed precision model. Make sure to keep your `poles` and `residues` in `float32` precision, especially for longer prompts or training. |
|
|
|
|
|
## Cite |
|
|
|
If you have found the pretrained models or architecture useful for you research or application, consider citing: |
|
``` |
|
@software{stripedhyena, |
|
title = {{StripedHyena: Moving Beyond Transformers with Hybrid Signal Processing Models}}, |
|
author = { Poli, Michael and Wang, Jue and Massaroli, Stefano and Quesnelle, Jeffrey and Carlow, Ryan and Nguyen, Eric and Thomas, Armin}, |
|
month = 12, |
|
year = 2023, |
|
url = { https://github.com/togethercomputer/stripedhyena }, |
|
doi = { 10.57967/hf/1595 }, |
|
} |
|
``` |
