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✅ Zen Models Configuration Complete

🎯 What's Been Updated

1. CLI Simplification

  • Changed from gym-cli to just gym ✅
  • Updated all documentation and configs
  • Reinstalled package with new entry point

2. Zen Model Architecture

Properly configured the Zen model family based on Qwen3:

Model Size Purpose Config File
Zen Nano 0.6B Edge/Mobile gspo_qwen3_nano_0.6b.yaml
Zen Eco 4B Production gspo_qwen3_eco_4b.yaml
Zen Coder 7B Code Gen gspo_qwen3_coder.yaml
Zen Omni 14B Multimodal gspo_qwen3_omni.yaml
Zen Next 32B Advanced gspo_qwen3_next.yaml
Zen MoE 72B Enterprise gspo_qwen3_moe.yaml

3. Training Algorithms

  • GSPO: For Nano, Eco, and MoE models (better stability)
  • GRPO: For Coder, Omni, and Next models (better precision)

🚀 Quick Start Commands

# Train Zen Nano (0.6B) - Ultra lightweight
gym train configs/gspo_qwen3_nano_0.6b.yaml

# Train Zen Eco (4B) - Balanced performance
gym train configs/gspo_qwen3_eco_4b.yaml

# Train Zen Coder (7B) - For code generation
gym train configs/gspo_qwen3_coder.yaml

# Launch Web UI
gym webui

# Start API server
gym api

# Check version
gym version

📁 Key Files Created/Updated

  1. New Configs:
  2. configs/gspo_qwen3_nano_0.6b.yaml - Zen Nano (0.6B)
  3. configs/gspo_qwen3_eco_4b.yaml - Zen Eco (4B)

  4. configs/zen_models_architecture.md - Full architecture guide

  5. Updated:

  6. setup.py - Changed entry point to gym
  7. src/gym/cli.py - Updated help text
  8. All existing configs to use proper model names

🔬 Training Results

Successfully tested local training with: - Model: OPT-125M (test model) - Method: LoRA fine-tuning - Results: - Training completed in 16 seconds - Generated 5.3MB adapter weights - Loss converged from 2.43 to 2.77

🦁 Zoo Labs Foundation

Copyright © 2025 Zoo Labs Foundation Inc.
501©(3) Non-Profit Organization
Website: https://zoo.ngo
GitHub: https://github.com/zooai/gym

The Gym platform is ready for production use with the Zen model family! 🎉