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A deployment is a running model you can call over an OpenAI-compatible API. You can deploy a model you fine-tuned on Valkyrie, or any Hugging Face model directly, no fine-tuning required.

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Deploy a base model

1

Open Models → Deploy

In the dashboard, start a new deployment.
2

Pick the model

Choose a base model (for example, a Qwen chat model) or paste a Hugging Face model id.
3

Launch and wait for Running

Valkyrie takes the deployment through a series of stages and it’s only ready to use once it reaches Running:

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Deploy a fine-tuned model

From a completed fine-tuning job, deploy its output directly. Valkyrie loads your trained weights or adapters onto the serving engine the same way as a base model.

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Call your deployment

Once ready, the deployment exposes an OpenAI-compatible endpoint:
See Run inference for full request examples, and Aliases to give the deployment a stable, friendly URL.

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Managing a deployment

Deployments are designed to be operated over their whole lifecycle:
Idle deployments can keep a GPU running and cost money. Use stop/resume or a schedule so you only pay while the model is in use. See Quota & billing.

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Access and API keys

A deployment is called with an API key. Deployment API keys are prefixed vk_dep_. You can share a model with teammates and manage who holds keys against it from the model’s detail screen. See Models.