pennydoesdev/Orb

Alkaid A

Fine-tuned from Qwen3.5-27B-Claude-4.6-Opus-Reasoning-Distilled with a custom multi-phase code review, debugging, and deployment workflow.

Capabilities

• Structured code review with pros/cons analysis
• 5-iteration debug cycle with variations
• Production deployment strategy generation
• Security, scalability, and compliance deep dives
• Automated versioning (00.00.XX) and GitHub release management
• Documentation generation and test automation

Alkaid A Workflow

1. Detailed code/plan feedback with pros and cons
2. Guided debug phase
3. Production deployment strategy
4. 5x debug iterations with variations
5. Security, scalability, compliance deep dive
6. API endpoint testing and monitoring
7. Help doc scraping and compatibility checks
8. GitHub versioned releases (00.00.XX)
9. Guided repository push
10. User testing, benchmarking, hardening
11. Developer documentation and automated tests
12. Progress summary and acknowledgment

Training

• Method: LoRA SFT (rank 16, alpha 16)
• Data: 2,326 Opus reasoning traces + custom workflow examples
• Quantization: 4-bit NF4 during training
• Framework: Transformers + PEFT + TRL
• Base Model: Jackrong/Qwen3.5-27B-Claude-4.6-Opus-Reasoning-Distilled

Usage

from transformers import AutoModelForCausalLM, AutoTokenizer

model = AutoModelForCausalLM.from_pretrained("pennydoesdev/Alkaid-A")
tokenizer = AutoTokenizer.from_pretrained("pennydoesdev/Alkaid-A")

Training Studio

Train your own version at: Alkaid-A-Studio

License

Apache 2.0