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Partner spotlight: How Cerebras accelerates AI app development
- With Cerebras’ high-speed inference endpoints, you can reduce latency, speed up model responses, and maintain quality at scale with models like Llama 3.1-70B.
- Cerebras tackles this challenge with optimized computations, streamlined data transfer, and intelligent decoding designed for speed.
- Cerebras Inference’s speed reduces the latency of AI applications powered by their models, enabling deeper reasoning and more responsive user experiences.
- By prioritizing performance, efficiency, and flexibility, the WSE-3 ensures faster, more consistent results during model performance.
- Integrating LLMs like Llama 3.1-70B from Cerebras into DataRobot allows you to customize, test, and deploy AI models in just a few steps.
- Deploying LLMs like Llama 3.1-70B with low latency and real-time responsiveness is no small task. But with the right tools and workflows, you can achieve both.
- This performance is powered by Cerebras’ third-generation Wafer-Scale Engine (WSE-3), a custom processor designed to optimize the tensor-based, sparse linear algebra operations that drive LLM inference.
- By following a few simple steps, you’ll be able to customize and deploy your own LLMs, giving you the control to optimize for both speed and quality.
- When combined with an intuitive development experience, you can reduce LLM latency for faster user interactions.
- Accessing these optimized models is simple — they’re hosted on Cerebras and accessible via a single endpoint, so you can start leveraging them with minimal setup.
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