Use Unsloth Studio from anywhere

Unsloth Studio is an open-source, no-code web UI for running, training, and exporting local models. When you run a model in Studio it serves an OpenAI-compatible API on your machine — by default at http://127.0.0.1:8888. That’s local only. Keep Studio on your machine and run the Tokios connector next to it: the connector dials out to https://api.tokios.com, and your tools, teammates, or agents call one authenticated endpoint from anywhere.

Beginner-friendly. Unsloth Studio is a point-and-click UI — pick a model, run it, and it’s serving. Along with Ollama and LM Studio, it’s one of the easiest ways to get a local model behind a Tokios endpoint.

The outbound-only way

Run a model in Unsloth Studio

Start Studio and load a model through its UI. Studio launches with:

unsloth studio -H 0.0.0.0 -p 8888

Once a model is running, Studio exposes an OpenAI-compatible API on port 8888. Leave it on your machine — you don’t need to open it to your network.

Pair the Tokios connector

Sign in at tokios.com/console, open the Setup tab, and click Start pairing. Tokios shows a one-time claim code like TKS-XXXX-XXXX, valid for about 15 minutes.On the machine running Studio, run the install one-liner for your OS:

irm https://tokios.com/downloads/install/windows | iex; tokios-install -Code 'TKS-XXXX-XXXX'

curl -fsSL https://tokios.com/downloads/install/macos | sh -s -- --code TKS-XXXX-XXXX

curl -fsSL https://tokios.com/downloads/install/linux | sh -s -- --code TKS-XXXX-XXXX

Already have tokios-connector installed? Pass the code directly instead:

tokios-connector TKS-XXXX-XXXX

Back in the console, approve the device on the Setup or Connectors tab. The connector’s token is delivered over the tunnel once approved — you never see it on screen or paste it into a file.

Point the connector at Studio's /v1 API

For the basic single-model path, enter Studio’s OpenAI-compatible endpoint as the upstream: http://127.0.0.1:8888/v1. If you’re serving several models through a tokios-connector.json config, set the upstream BaseUrl explicitly:

{
  "Upstream": {
    "BaseUrl": "http://127.0.0.1:8888/v1"
  }
}

See Connector config for the full multi-model file format.

In the Models tab, register the model and choose a public name — for example, studio-tunnel. That public name, not the model id inside Studio, is what clients send in the model field.

Create an API key

In the Keys tab, click Create key. Optionally scope it to specific deployments with model-name patterns (comma-separated globs, * for all). Copy the sk-tok-… key now — it’s shown only once.

Use it from anywhere

Once you have a deployment name and an API key, any OpenAI- or Anthropic-compatible client can reach the model you’re running in Studio — from another machine, a teammate’s laptop, or a hosted agent.

curl https://api.tokios.com/v1/chat/completions \
  -H "Authorization: Bearer sk-tok-YOUR_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "studio-tunnel",
    "stream": true,
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

from openai import OpenAI

client = OpenAI(
    base_url="https://api.tokios.com/v1",
    api_key="sk-tok-YOUR_KEY",
)

response = client.chat.completions.create(
    model="studio-tunnel",
    messages=[{"role": "user", "content": "Hello!"}],
    stream=True,
)

for chunk in response:
    print(chunk.choices[0].delta.content or "", end="")

export ANTHROPIC_BASE_URL=https://api.tokios.com
export ANTHROPIC_API_KEY=sk-tok-YOUR_KEY
claude --model studio-tunnel

The model field is always your registered deployment name (studio-tunnel above), never the model id inside Studio. Fine-tuned a model in Studio and exported it to GGUF? See Serve a fine-tune for the same endpoint flow.

FAQ

Does streaming work?

Yes. Set "stream": true and Tokios returns standard server-sent events (SSE) in OpenAI or Anthropic format, depending on which API surface you called.

Can I use a model I trained in Studio?

Yes. Run it in Studio the same way, or export it to GGUF and serve it through Ollama or llama.cpp — either way, register it as a Tokios deployment. See Serve a fine-tune.

Your model never leaves your machine — your endpoint works everywhere

Unsloth Studio keeps running on your machine, with no inbound ports and nothing exposed to the network. The connector only dials out. Everything past that — auth, routing, streaming — is one endpoint you can call from any machine, teammate, or agent you choose to give a key to.

Quickstart

Pair a connector and register your first model end to end.

Serve a fine-tune

Turn a model you trained into a private API endpoint.

Hardware & fit

Serve & connect your runtime

Connect a client or app

Compare

Use Unsloth Studio from anywhere — safely

The outbound-only way

Use it from anywhere

FAQ

Your model never leaves your machine — your endpoint works everywhere

Quickstart

Serve a fine-tune

​The outbound-only way

​Use it from anywhere

​FAQ

​Your model never leaves your machine — your endpoint works everywhere

Quickstart

Serve a fine-tune

The outbound-only way

Use it from anywhere

FAQ

Your model never leaves your machine — your endpoint works everywhere