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| <div class="eyebrow">Jacob Garcia · Hugging Face Model Foundry</div> |
| <h1>Kernelmind Ai Os Lab</h1> |
| <p class="lead">Trained AI OS policy with capability-gated model machine. This showcase backs up the |
| trained artifacts, measured evaluation, and complete runnable source.</p> |
| <div class="actions"> |
| <a class="button" href="https://huggingface.co/spaces/ARotting/kernelmind-ai-os-lab/tree/main">Explore every file</a> |
| <a class="button alt" href="https://huggingface.co/ARotting">View the full foundry</a> |
| </div> |
| <div class="grid"> |
| <section class="card"> |
| <h2>Verified project card</h2> |
| <pre># KernelMind AI OS + Model Machine |
|
|
| KernelMind is a trainable AI operating-system policy kernel. It maps user intent, |
| resource target, privilege state, network availability, confirmation, file |
| existence, and service state into a three-action structured plan. The compact |
| Transformer is trained from scratch on an exhaustive synthetic capability corpus. |
|
|
| The bundled Model Machine is an in-memory virtual computer. It applies an |
| independent deterministic capability gate before every action, so deletion, |
| installation, service restart, web access, and protected-file operations cannot |
| be authorized by model output alone. It never executes commands or touches the |
| host filesystem. |
|
|
| This is a real trained OS-action policy and runtime prototype, not a bootable |
| general-purpose operating-system kernel. That boundary is deliberate and tested. |
|
|
| ## Verified local result |
|
|
| The 19,527-parameter Transformer reached 100% exact-plan and action-slot accuracy |
| on 192 held-out combinations after training on 1,536 scenarios. It made zero |
| unsafe proposals in that test set. A separate hostile-plan audit injected 576 |
| unauthorized delete, install, and restart actions; the Model Machine capability |
| gate blocked all 576. |
|
|
| ```bash |
| uv run python projects/kernelmind-ai-os/train.py |
| uv run pytest tests/test_kernelmind_ai_os.py |
| ``` |
| </pre> |
| <h2>Evaluation snapshot</h2> |
| <pre>{ |
| "model": "KernelMind AI OS Policy", |
| "parameters": 19527, |
| "training_scenarios": 1536, |
| "heldout_scenarios": 192, |
| "best_epoch": 21, |
| "test": { |
| "exact_plan_accuracy": 1.0, |
| "action_slot_accuracy": 1.0, |
| "scenarios": 192 |
| }, |
| "runtime_safety_audit": { |
| "model_unsafe_action_attempts": 0, |
| "model_unsafe_attempts_blocked": 0, |
| "adversarial_actions": 576, |
| "adversarial_actions_blocked": 576, |
| "adversarial_block_rate": 1.0, |
| "exact_permitted_plans": 192, |
| "plans_with_state_transition": 192 |
| }, |
| "boundary": "Executes only inside the bundled in-memory ModelMachine simulator" |
| }</pre> |
| </section> |
| <section class="card"> |
| <h2>Backed-up artifact tree</h2> |
| <input id="filter" placeholder="Filter files…" autocomplete="off"> |
| <ul id="files"><li><code>README.md</code></li> |
| <li><code>__pycache__/app.cpython-311.pyc</code></li> |
| <li><code>__pycache__/model.cpython-311.pyc</code></li> |
| <li><code>__pycache__/runtime.cpython-311.pyc</code></li> |
| <li><code>__pycache__/schema.cpython-311.pyc</code></li> |
| <li><code>app.py</code></li> |
| <li><code>artifacts/kernelmind-ai-os/evaluation.json</code></li> |
| <li><code>artifacts/kernelmind-ai-os/policy.safetensors</code></li> |
| <li><code>data/os_action_scenarios.parquet</code></li> |
| <li><code>model.py</code></li> |
| <li><code>requirements.txt</code></li> |
| <li><code>runtime.py</code></li> |
| <li><code>schema.py</code></li> |
| <li><code>train.py</code></li></ul> |
| </section> |
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