Using Gemma 7B Instruct on Together AI
Implementation guide · Gemma · Google DeepMind
Quick Start
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Code Examples
pip install togetherTOGETHER_API_KEYgemma-7b-itTogether 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="gemma-7b-it",
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 Gemma 7B Instruct
Gemma 7B Instruct is a cutting-edge large language model developed by Google DeepMind, boasting 7 billion parameters. As part of the Gemma family, it benefits from the advanced research underpinning Google's Gemini models. This model is optimized for text generation tasks, excelling in areas like question answering and summarization, and it is finely tuned to follow instructions effectively. Despite its compact size, Gemma 7B Instruct performs impressively on benchmarks, making it versatile for deployment across various hardware platforms, from laptops to cloud infrastructure. Moreover, it is open-source, with accessible weights and incorporates responsible AI practices, such as data filtering and human feedback, to ensure safe and ethical use.