INITIALIZING NEURAL HARNESS...

Loading Unsloth Triton Kernels & MoE Layer Router Maps

AI-TRAINER

UNSLOTH GRPO MOE

Proxify-ADB Autonomous Fleet Router & MoE Weight Shedder

GPU VRAM: 6.2 / 16.0 GB
MoE Stream RAM: 34.5 / 64.0 GB
ADB Fleet: 14 / 14 Connected

AUTONOMOUS UN SLOTH GRPO PIPELINE MAP

Real-time dynamic expert pruning, hard execution sandbox evaluation, and GGUF quant deployment

STATUS: IDLE
Overall Progress: 0%

UNSLOTH GRPO HARD EXECUTION REWARD CONVERGENCE

Multi-vector reward curve ($R_{exec} = +3.0$, $R_{anti-hesit} = +2.0$, Safety = $-10.0$)

Step 0 / 300

DOMAIN MoE EXPERT RETENTION VS PRUNED TRIVIA EXPERTS

Dropping ~68.75% dormant botany/history experts across 61 layers

Retained: 64 / 256

10.30.20.0/24 PROXMOX FLEET TOPOLOGY

vmbr1 Isolated
Gateway Control Node 10.30.20.1
Port 5555 / REST API
Dynamic DHCP Pool .100 ──► .254
dnsmasq 12h Leases

PIPELINE SCRIPT INSPECTOR

# Select a script to view source code...
LIVE LOG STREAM CONSOLE 0 Logs
LEVEL:

TUNING KNOBS & REWARD WEIGHTS

Hardware Memory Target: 16.0 GB VRAM + 64.0 GB System RAM Streaming