Using StripedHyena Nous 7B on Together AI
Implementation guide · Striped Hyena · Together.ai
Quick Start
- 1
- 2Use the Together AI SDK or REST API to call
stripedhyena-nous-7b— see the documentation for request format. - 3
Code Examples
pip install togetherTOGETHER_API_KEYstripedhyena-nous-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-nous-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 Nous 7B
StripedHyena-Nous-7B (SH-N 7B) is a state-of-the-art large language AI model from Together Computer, developed alongside Nous Research. Diverging from the traditional Transformer-based architecture, SH-N 7B employs a unique design integrating multi-head, grouped-query attention with gated convolutions in structured Hyena blocks. This hybrid architecture enhances its capacity for long-context processing and offers superior training efficiency and decoding speeds. The model is adept in chat applications, capable of engaging in coherent long-form dialogues, answering questions, and performing various language tasks. Despite requiring specific hardware configurations, SH-N 7B presents competitive performance comparable to leading open-source Transformer models. It’s trained on extensive datasets, including RedPajama, optimized for both short and long-context sequences up to 32k tokens.