Using Nous Hermes Llama 2 7B on Fireworks AI
Implementation guide · Hermes · Nous Research
Fireworks AI exposes Nous Hermes Llama 2 7B through model ID accounts/fireworks/models/nous-hermes-llama2-7b. Use the setup steps, sourced pricing, capabilities, and official provider links below to validate this route before deployment.
Last refreshed 2026-04-19. Next refresh: weekly.
Quick Start
- 1
- 2Use the Fireworks AI SDK or REST API to call
accounts/fireworks/models/nous-hermes-llama2-7b— see the documentation for request format. - 3
Code Examples
pip install openaiFIREWORKS_API_KEYaccounts/fireworks/models/nous-hermes-llama2-7bFireworks model IDs use "accounts/fireworks/models/{model-name}" format, e.g. "accounts/fireworks/models/llama4-scout-instruct-basic" or "accounts/fireworks/models/deepseek-r1".
import os
from openai import OpenAI
client = OpenAI(
api_key=os.environ["FIREWORKS_API_KEY"],
base_url="https://api.fireworks.ai/inference/v1"
)
response = client.chat.completions.create(
model="accounts/fireworks/models/nous-hermes-llama2-7b",
messages=[{"role": "user", "content": "Hello"}]
)
print(response.choices[0].message.content)Pricing on Fireworks 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.