# FAQ > Short answers about what Retoque does, what it doesn't, and what is still planned. Source: https://retoque.xyz/docs/faq Markdown: https://retoque.xyz/docs/md/faq ## Does Retoque run my model? No. You download the base model from Hugging Face and run it on your own hardware or a host you control. Retoque distributes the adapter, the evidence and the license, and the CLI loads everything locally. There is no hosted inference. ## Is the registry key an OpenAI, Anthropic or Hugging Face key? No. A key starting with `rtq_` authenticates you to the Retoque registry for license checks and downloads. It can't call any model and is never sent to a model host. ## Which models are supported? One base model at first release: `Qwen/Qwen2.5-1.5B-Instruct` at commit `989aa7980e4cf806f80c7fef2b1adb7bc71aa306`. The live list is on [Supported models](https://retoque.xyz/models) and at `GET /api/v1/models`. Other sizes, revisions and quantized variants are not supported. ## Can I use a patch on a different revision or a quantized model? Not as a supported install. The CLI refuses anything except the exact repository and commit unless you pass `--experimental-override`, which is recorded in `retoque.lock`. Results for that combination are unknown. ## Does installing a patch change my base model? No. The base weights are only read. A patch is a separate adapter file, and `retoque disable` returns you to the pure base model without reinstalling anything. ## How do I know a patch works? Read its evaluation on the patch page: the held-out baseline and patched counts out of the full suite, the prompt-only control, the regressions introduced, and whether rollback reproduced the base outputs. The evidence state says how far it has been checked. See [Evaluation methodology](https://retoque.xyz/docs/evaluation). ## Why can't I see the held-out cases? Publishing them would let anyone tune a later version against the benchmark. The suite's sha256 is published instead, and reviewers with access can reproduce the run. Cases shown on a patch page come from the validation split. ## What does the signature prove? That a trusted publisher signed these exact bytes. It says nothing about output quality. See [Artifacts and verification](https://retoque.xyz/docs/artifacts). ## Is the onchain license live? The registry and license market contracts are written and tested, and run on a local development chain. They are not deployed to Robinhood Chain mainnet. Mainnet waits on an independent security review. Free click-through licenses work today. See [Robinhood Chain](https://retoque.xyz/docs/robinhood-chain). ## Can a license be revoked after I download? Revoking or suspending a license stops new downloads. It can't recall files already on your disk. The license terms still govern how you use them. ## Can I resell a license? Onchain licenses are bound to the buyer's wallet inside the contract and are not tokens, so there is nothing to transfer. Free licenses are tied to your account. ## Can I serve a patch to my users? Only if the version's terms allow it. Check the commercial scope on the patch page. Technically, serve it with static adapters as described in [Serving with vLLM](https://retoque.xyz/docs/vllm), which is untested for published patches. ## Can I build my own patch? Yes, in the creator studio. Upload a JSONL dataset with families, train with the fixed configuration, evaluate, and submit for review. See the [Creator guide](https://retoque.xyz/docs/creators). Training runs on operator hardware for now. Hosted GPU workers are planned. ## Can I tune the training hyperparameters? No. Every studio run uses one bounded LoRA configuration, so results across patches are comparable and reviewable. ## Is there a way to remove an installed patch? There is no uninstall command in CLI 0.1.0. `retoque disable` stops it from loading. To free the space, delete `~/.retoque/patches//` yourself. ## Where can my assistant read these docs? Every page is available as Markdown at `/docs/md/`. [/llms.txt](https://retoque.xyz/llms.txt) indexes them, and `/llms-full.txt` has all of them in one file. `GET /docs/search?q=` returns ranked sections as JSON.