> For the complete documentation index, see [llms.txt](https://docs.scorable.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.scorable.ai/concepts-and-examples/cookbooks/connect-a-model.md).

# Connect a model

Scorable subscription provides [a set of models](https://scorable.ai/settings/llm-accounts) you can use in your Judges and proxy. You are not limited by that selection, though. Integrating with cloud providers' models or connecting to locally hosted models is possible via UI, the [CLI](/concepts-and-examples/cookbooks/cli.md#custom-model-management), [SDK](https://sdk.scorable.ai/examples.html#add-a-model), or REST API.

{% hint style="info" %}
[Full model list](https://api.scorable.ai/public-models/).
{% endhint %}

### Huggingface example

To use an [HF inference endpoint](https://huggingface.co/docs/inference-endpoints/index), add the model endpoint via the SDK or through the REST API

```bash
curl --request POST \
     --url https://api.scorable.ai/v1/models/ \
     --header 'Authorization: Api-Key $SCORABLE_API_KEY' \
     --header 'accept: application/json' \
     --header 'content-type: application/json' \
     --data '
               {
                 "name": "huggingface/meta-llama/Meta-Llama-3-8B",
                 "url": "https://my-endpoint.huggingface.cloud",
                 "default_key": "$HF_KEY"
               }
            '
```

After adding the model, you can use it like any other model in your evaluators.

```python
evaluator = client.evaluators.create(
    name="My model test", scoring_criteria="Hello, my model!", model="huggingface/meta-llama/Meta-Llama-3-8B"
)
```