license: apache-2.0
base_model:
- meta-llama/Llama-3.1-8B-Instruct
pipeline_tag: text-generation
tags:
- medical
- code
Xea-Llama
🚀 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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🔍 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.
📌 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.
🏆 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 prompts—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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For any issues, feel free to open a GitHub issue on our repository.