Using Nous Hermes Llama 2 7B on Together AI
Implementation guide · Hermes · Nous Research
Together AI exposes Nous Hermes Llama 2 7B through model ID nous-hermes-llama2-7b. Use the setup steps, sourced pricing, capabilities, and official provider links below to validate this route before deployment.
Last refreshed 2026-06-15. Next refresh: weekly.
Quick Start
- 1
- 2Use the Together AI SDK or REST API to call
nous-hermes-llama2-7b— see the documentation for request format. - 3
Code Examples
pip install togetherTOGETHER_API_KEYnous-hermes-llama2-7bTogether 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="nous-hermes-llama2-7b",
messages=[{"role": "user", "content": "Hello"}]
)
print(response.choices[0].message.content)Pricing on Together AI
| Type | Price (per 1M) |
|---|---|
| Input tokens | $0.20 |
| Output tokens | $0.20 |
Capabilities
About Nous Hermes Llama 2 7B
The Nous Hermes Llama 2 7B is a state-of-the-art large language model built on the efficient Llama 2 transformer architecture. Fine-tuned on over 300,000 instructions, it exhibits several impressive features, such as generating long, detailed responses with a low hallucination rate. Notably, it lacks OpenAI's censorship, enabling more open discussions. The model excels in knowledge retention and task completion through extensive training on synthetic GPT-4 outputs and supports prompts in the versatile Alpaca format. Its benchmark performance varies across tasks like GPT4All and BigBench, and quantized versions are available, providing flexible deployment across various platforms.