> For the complete documentation index, see [llms.txt](https://docs.roboflow.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/supported-models/dino-v3.md).

# Dino v3

Meta의 [DINOv3](https://github.com/facebookresearch/dinov3) 를 통한 분류용 자기지도 비전 모델 [Serverless Hosted API](/roboflow/roboflow-ko/deploy/serverless-hosted-api-v2.md). DINOv3는 Roboflow에서 linear probe classifier를 학습하여 데이터셋에 맞게 조정할 수 있는 강력한 범용 시각 특징을 생성합니다.

공개 DINOv3 별칭은 없습니다. 데이터셋에서 직접 DINOv3 classifier를 학습하고, 이를 당신의 `{model_id}/{version}`.

## 코드 샘플

다음을 설치하세요: [Inference SDK](https://inference.roboflow.com/):

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

전달하세요 [Roboflow API Key를](https://app.roboflow.com/settings/api) 다음을 통해 `API_KEY` env 변수에 넣고, 다음을 바꾸세요 `your-project/1` 자신의 model ID와 version으로.

```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="your-project/1")
print(results)
```

{% hint style="info" %}
설정하세요 `api_url` 를 배포 대상에 맞게:

* `https://serverless.roboflow.com` 은 Serverless Hosted API용입니다.
* `http://localhost:9001` 로컬 [Inference](https://inference.roboflow.com/) 서버용입니다.
* 귀하의 [Dedicated Deployment](/roboflow/roboflow-ko/deploy/dedicated-deployments.md) 비공개 엔드포인트용 URL입니다.
  {% endhint %}

자체 호스팅 배포 및 추가 세부 정보는 다음을 참조하세요 [Inference 문서](https://inference.roboflow.com/).


---

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