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Together AI

Using StripedHyena Hessian 7B on Together AI

Implementation guide · Striped Hyena · Together.ai

Serverless

Quick Start

  1. 1
    Create an account at Together AI and generate an API key.
  2. 2
    Use the Together AI SDK or REST API to call stripedhyena-hessian-7b — see the documentation for request format.
  3. 3
    You'll be billed $0.20/1M input, $0.20/1M output tokens. See full pricing.

Code Examples

Install
pip install together
API key
TOGETHER_API_KEY
Model ID
stripedhyena-hessian-7b

Together 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

TypePrice (per 1M)
Input tokens$0.20
Output tokens$0.20

Capabilities

Structured Outputs

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.

Model Specs

Released2023-12-08
Parameters7B
Context32K
ArchitectureDecoder Only

Provider

Together AI
Together AI

San Francisco, California, United States