Using ReMM SLERP L2 13B on Together AI
Implementation guide · Re:MythoMax · Undi95
Together AI exposes ReMM SLERP L2 13B through model ID remm-slerp-l2-13b. 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
remm-slerp-l2-13b— see the documentation for request format. - 3
Code Examples
pip install togetherTOGETHER_API_KEYremm-slerp-l2-13bTogether 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="remm-slerp-l2-13b",
messages=[{"role": "user", "content": "Hello"}]
)
print(response.choices[0].message.content)Pricing on Together AI
| Type | Price (per 1M) |
|---|---|
| Input tokens | $0.30 |
| Output tokens | $0.30 |
Capabilities
About ReMM SLERP L2 13B
The ReMM SLERP L2 13B, developed by Undi95, is a large language model that reimagines the original MythoMax-L2-B13 with enhanced architecture and techniques. Utilizing the SLERP method, it combines foundational models like Mythologic and Huginn to boost performance and versatility in natural language processing tasks. Built on the Llama architecture with 13 billion parameters, it effectively handles complex language scenarios with a context length of 4096 tokens.