Instructions to use Ittirit-delentia/DLT-system-devops-lora-draft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Ittirit-delentia/DLT-system-devops-lora-draft with PEFT:
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- Notebooks
- Google Colab
- Kaggle
| license: apache-2.0 | |
| base_model: Delentia/delentia-slm-jitna-v0.4 | |
| tags: | |
| - lora | |
| - peft | |
| - devops | |
| - rct-analyst | |
| - system-triage | |
| - mirror-mode | |
| - self-evolving | |
| - microservices | |
| # Delentia SLM — System DevOps & RCT Analyst v0.4 (DLT-system-devops-lora-draft) | |
| > [!NOTE] | |
| > **ONLINE DRAFT / STAGING SANDBOX (ระบบแบบร่างออนไลน์):** | |
| > โมเดลนี้อยู่ภายใต้ขั้นตอนการทดสอบและจัดทำดราฟท์โครงสร้างสถาปัตยกรรม (Sandbox Staging Phase) สำหรับพัฒนาต่อยอดจากโมเดลหลักขององค์กร ปัจจุบันจะแสดงผลเฉพาะเอกสารคุณสมบัติ (README) เท่านั้น โดยไฟล์น้ำหนักโมเดลจริงจะถูกพุชเข้าระบบหลังจากผ่านการทดสอบและฝึกสอน (Fine-tuning) เป็นที่เรียบร้อย | |
| The System DevOps & RCT Analyst is a diagnostic system-management PEFT LoRA adapter for **Delentia OS v0.4**. Working in **Adversarial Mirror Mode**, it parses system telemetry logs, challenges bottlenecks, and generates JITNA kernel configuration outputs to self-heal microservice states and optimize resource scheduling. | |
| ## 🔗 Platform Dependencies | |
| This adapter must be loaded dynamically on the system's cognitive core: | |
| * **Base Engine:** [Delentia/delentia-slm-jitna-v0.4](https://huggingface.co/Delentia/delentia-slm-jitna-v0.4) (Official Org Core) | |
| * **Official System Portal:** [Delentia Labs](https://huggingface.co/Delentia) | |
| --- | |
| ## 🚀 Runtime Input/Output Examples (ตัวอย่างการรันไทม์) | |
| ### Example 1: Resolving VRAM Saturation Warning | |
| * **Prompt (Input):** | |
| > Analyze telemetry logs: node_4500 experienced VRAM Saturation (94% utilization). Scribe compression is at 3.5x. Recommend mitigation. | |
| * **Completion (Output):** | |
| ```json | |
| { | |
| "system_alert": "VRAM_CRITICAL_WARNING", | |
| "root_cause": "Low Scribe compression ratio under heavy context query loops.", | |
| "recommended_action": "Trigger recursive Scribe delta compression sequence, target compression ratio >= 30.96x.", | |
| "nodes_to_restart": ["node_4500_scribe_executor"] | |
| } | |
| ``` | |
| ### Example 2: Challenge Latency Bottlenecks (Adversarial Mirror Mode) | |
| * **Prompt (Input):** | |
| > Adversarial Query: "Why is node_4500 suffering from high latency? The CPU utilization is only 12%. Challenge the assumption that hardware is the bottleneck." | |
| * **Completion (Output):** | |
| > I: challenge hardware bottleneck | D: cpu: 12%, latency: high | Δ: buffer_size: adjusted | A: TriggerMirrorAnalysis() | R: Adversarial synthesis: Latency is caused by Scribe memory lock contention, not hardware capacity | M: mitigation: reconfigure scribe lock to non-blocking mode | |
| --- | |
| ## Technical Specifications | |
| * **Fine-Tuning Method:** System-Triage instruction QLoRA (r=32, alpha=64) | |
| * **Diagnostic Range:** Monitors up to 33 microservices (Infrastructure, Core Processing, GAIA integrations, support) | |
| * **Inference Latency:** **< 12ms** swap and execution. |