# ResNet

Run ImageNet-pretrained ResNet image classification through the [Serverless Hosted API](/deploy/serverless-hosted-api-v2.md), or self-host using [Roboflow Inference](https://inference.roboflow.com/).

## Default aliases

Pass any of these aliases as the `model_id` when using the [inference-sdk](/deploy/serverless-hosted-api-v2/use-with-python-sdk.md):

* `resnet18`
* `resnet34`
* `resnet50`
* `resnet101`

## Code sample

Install the SDK:

```bash
pip install inference-sdk
```

The sample below runs `resnet50` against a remote image. Pass [Roboflow's API Key](https://app.roboflow.com/settings/api) via the `API_KEY` env variable.

```python
import os
import urllib.request
from inference_sdk import InferenceHTTPClient

image_url = "https://media.roboflow.com/notebooks/examples/dog.jpeg"
image_path = "dog.jpeg"
urllib.request.urlretrieve(image_url, image_path)

client = InferenceHTTPClient(
    api_url="https://serverless.roboflow.com",
    api_key=os.getenv("API_KEY"),
)
results = client.infer(image_path, model_id="resnet50")
print(results)
```

{% hint style="info" %}
Set `api_url` to match your deployment target:

* `https://serverless.roboflow.com` for the Serverless Hosted API.
* `http://localhost:9001` for a local [Inference](https://inference.roboflow.com/) server.
* Your [Dedicated Deployment](/deploy/dedicated-deployments.md) URL for a private endpoint.
  {% endhint %}


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```
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```

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