Using OpenHermes 2.5 Mistral 7B on Together AI
Implementation guide · OpenHermes 2 · Teknium
Quick Start
- 1
- 2Use the Together AI SDK or REST API to call
openhermes-2.5-mistral-7b— see the documentation for request format. - 3
Code Examples
pip install togetherTOGETHER_API_KEYopenhermes-2.5-mistral-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="openhermes-2.5-mistral-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
No model capability flags are currently sourced.
About OpenHermes 2.5 Mistral 7B
OpenHermes 2.5 Mistral 7B is an advanced large language model developed by Teknium, building on the previous version, OpenHermes 2. Utilizing a transformer architecture, it's fine-tuned on over one million entries, combining code and non-code data, primarily composed of GPT-4 generated text. This enhances its human-like response capabilities across diverse contexts. It excels in conversational AI with its multi-turn dialogue support through the ChatML format, significantly improves in code generation tasks with a high HumanEval score, and performs robustly on benchmarks like GPT4All and AGIEval. Additionally, it offers various quantization options for optimized hardware performance and is adept at real-time data processing, making it ideal for customer service and immediate data analysis applications.