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CePO (Cerebras Planning & Optimization) is a framework that adds advanced reasoning capabilities to the Llama family of models by utilizing test-time compute. This approach enables Llama to address complex reasoning tasks that can be difficult for standard one-shot or instruct models. CePO is implemented using Cerebras inference, delivering high-throughput speeds that enable efficient test-time computation for more sophisticated reasoning tasks.

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How CePO Works

CePO demonstrates how additional test-time computation can improve Llama’s reasoning. The process involves four main stages:
  1. Planning: The LLM produces a plan to solve a given problem step by step.
  2. Execution: The LLM executes the plan multiple times, generating multiple responses.
  3. Analysis: The model analyzes the responses to detect inconsistencies across executions, helping catch and correct mistakes.
  4. Best-of-N: Responses are evaluated within a Best-of-N framework that includes a structured confidence scoring mechanism.

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Get Started with CePO

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Step 1: Prerequisites

CePO is built on the popular, open-source OptiLLM library. To get started, install OptiLLM and make sure you have the latest version of the Cerebras Inference SDK installed.
Next, configure your API key, which can be found in our developer platform.
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Step 2: Run OptiLLM with CePO

Finally, run the OptiLLM script with CePO
If you would like to print intermediate states in the OptiLLM log, you can optionally add:

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Continued Research

Further work on CePO includes:
  • More advanced prompting frameworks that leverage comparative reasoning.
  • Synthetic data optimized for inference-time computation.
  • Enhanced verification mechanisms for complex reasoning chains.
If you have questions or would like to discuss your findings, please join the #research channel in our discord community.

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Read More

For more information on the implementation details and results, see the full CePO announcement.