Using StripedHyena Hessian 7B on Together AI
Implementation guide · Striped Hyena · Together.ai
Quick Start
- 1
- 2Use the Together AI SDK or REST API to call
stripedhyena-hessian-7b— see the documentation for request format. - 3
Code Examples
pip install togetherTOGETHER_API_KEYstripedhyena-hessian-7bTogether uses "organization/model-name" format, e.g. "meta-llama/Llama-4-Scout-17B-16E-Instruct" or "Qwen/QwQ-32B". See the Together model catalog for the exact ID.
from together import Together
client = Together() # reads TOGETHER_API_KEY from env
response = client.chat.completions.create(
model="stripedhyena-hessian-7b",
messages=[{"role": "user", "content": "Hello"}]
)
print(response.choices[0].message.content)About Together AI
Platform for running open-source and proprietary LLMs
Together AI is a platform for running open-source and proprietary LLMs with fast serverless and dedicated endpoints at competitive inference pricing.
Pricing on Together AI
| Type | Price (per 1M) |
|---|---|
| Input tokens | $0.20 |
| Output tokens | $0.20 |
Capabilities
About StripedHyena Hessian 7B
The StripedHyena Hessian 7B (SH 7B) is a cutting-edge large language model developed by Together Computer. It employs a hybrid architecture that integrates multi-head, grouped-query attention, and gated convolutions arranged in Hyena blocks, distinguished from traditional Transformer models by its enhanced performance and efficiency 12. Designed for superior long-context processing, the model features a state-space model (SSM) layer for efficient inference and reduced memory usage 10, excelling in tasks like multi-document question answering and long-form text summarization. It supports sequences up to 32k tokens, ensuring fast decoding and high throughput, and even includes a variant, SH-N 7B, tailored for chat applications 2. Despite its strengths, it requires custom kernels outside its playground, is a mixed-precision model, and ongoing research is needed to explore further improvements 1.