HUMIGENCE_COMMAND_READY.md

Humigence Command - Ready to Use! 🚀

✅ Yes, you can launch this with "humigence"!

The Humigence training pipeline has been successfully refactored and is now ready to use with the humigence command.

🎯 How to Use

Launch Humigence CLI

humigence

What You'll See

──────────────── Humigence — Your AI. Your pipeline. Zero code. ────────────────
A complete MLOps suite built for makers, teams, and enterprises.

Options:
1. Supervised Fine-Tuning ✅
2. RAG Implementation (coming soon)
3. EnterpriseGPT (coming soon)
4. Batch Inference (coming soon)
5. Context Length (coming soon)
6. Exit

Select an option: 

Training Options

1. Select "1. Supervised Fine-Tuning"
2. Choose Setup Mode: Basic or Advanced
3. Select Model: TinyLlama, Qwen, Phi-2, etc.
4. Choose Training Recipe: LoRA, QLoRA, etc.
5. Select Dataset: Your available datasets
6. Choose Training Mode: Multi-GPU or Single-GPU
7. Confirm Configuration: Review and start training

🚀 What's New (Accelerate Refactor)

Clean Architecture

• Hugging Face Accelerate: Stable DDP training
• Single-GPU Evaluation: Always on cuda:0
• No More NCCL Errors: Robust distributed training
• Clean Code: Removed over-engineering

Key Features

• ✅ Multi-GPU Training: 2× RTX 5090s support
• ✅ Single-GPU Fallback: Automatic fallback if needed
• ✅ LoRA/QLoRA Support: Parameter-efficient fine-tuning
• ✅ Structured Logging: Clean, readable output
• ✅ Error Handling: Robust error management

📋 Training Modes

Multi-GPU Training (Recommended)

• Uses accelerate launch with 2× RTX 5090s
• Stable DDP training with NCCL backend
• Automatic device management
• Mixed precision (bf16/fp16)

Single-GPU Training

• Uses python train.py for single GPU
• Fallback option if multi-GPU fails
• Same functionality, single device

🎯 Usage Examples

Interactive CLI

humigence
# Select option 1
# Choose Multi-GPU Training
# Follow the configuration wizard

Direct Training (Advanced)

# Multi-GPU
accelerate launch --config_file accelerate_config.yaml train.py --config_file config.json

# Single-GPU
python train.py --config_file config.json

🔧 Technical Details

Files Created/Updated

• train.py - Clean Accelerate-based training script
• accelerate_config.yaml - Multi-GPU configuration
• cli/main.py - Updated CLI integration
• humigence - Command-line entry point

Dependencies

• Hugging Face Accelerate - Distributed training
• Transformers - Model loading and training
• PEFT - LoRA/QLoRA support
• Rich - Beautiful CLI interface

🎉 Ready to Use!

The Humigence training pipeline is now:

• ✅ Refactored with Hugging Face Accelerate
• ✅ Tested and working correctly
• ✅ Installed as humigence command
• ✅ Ready for production use

Just run humigence and start training! 🚀

📊 What You Get

1. Clean CLI Interface - Easy to use
2. Stable Multi-GPU Training - No more NCCL errors
3. Single-GPU Evaluation - No device mismatches
4. Structured Reporting - Clear training summaries
5. Error Handling - Robust error management
6. Production Ready - Works with your 2× RTX 5090s

The refactored Humigence pipeline is ready for your AI training needs! 🎯