Xea-Llama



πŸš€ Introduction

Xea-Llama is a next-generation AI model developed by EnhanceAI. It is designed for advanced reasoning, code generation, and problem-solving tasks. Built using reinforcement learning (RL) without supervised fine-tuning (SFT), Xea-Llama demonstrates powerful reasoning capabilities, self-verification, and structured chain-of-thought (CoT) processes.

Xea-Llama is fully open-source and optimized for superior performance, surpassing previous benchmarks in various AI domains.

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πŸ” Model Summary

Post-Training: Large-Scale RL

Xea-Llama follows a pure RL approach, which allows it to develop unique reasoning strategies without requiring supervised fine-tuning as a preliminary step. This approach results in highly optimized performance for complex reasoning tasks.

Our pipeline consists of:

  • Two RL stages for reasoning enhancement and alignment with human preferences.
  • Two SFT stages to develop base reasoning and general capabilities.

This pipeline ensures state-of-the-art performance across multiple domains, including math, code, and logical problem-solving.


πŸ“Œ Model Downloads

Xea-Llama is available for public access:

Xea-Llama Models

  • Base Model: Pre-trained model optimized for RL-based reasoning.
  • Distilled Models: Efficient, lightweight versions fine-tuned for deployment.

πŸ† Evaluation Results

Xea-Llama has been extensively tested across multiple benchmarks, achieving superior performance compared to previous models. It supports a maximum generation length of 32,768 tokens, making it ideal for long-form reasoning and complex tasks.

For benchmarking:

  • Temperature: 0.5 - 0.7 (Recommended: 0.6).
  • Avoid system promptsβ€”instructions should be in the user prompt.
  • Mathematical reasoning should be encouraged using: "Please reason step by step and put your final answer within \boxed{}."
  • Multiple test iterations are recommended for accurate evaluations.

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