> 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/smolvlm2.md).

# SmolVLM2

SmolVLM2는 HuggingFace의 컴팩트한 비전-언어 모델입니다. 이미지와 텍스트 프롬프트를 받아 텍스트 응답을 반환합니다.

{% hint style="info" %}
SmolVLM2는 Serverless Hosted API에서 사용할 수 없습니다. 다음에서 실행하세요. [Dedicated Deployment](/roboflow/roboflow-ko/deploy/dedicated-deployments.md) 또는 [자체 호스팅 Inference](https://inference.roboflow.com/).
{% endhint %}

## 코드 샘플

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

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

설정하세요 `api_url` 를 Dedicated Deployment URL 또는 로컬 Inference 서버로 설정하세요. 다음을 전달하세요 [Roboflow API Key](https://app.roboflow.com/settings/api) 를 `API_KEY` 환경 변수.

```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://your-deployment.roboflow.cloud",
    api_key=os.getenv("API_KEY"),
)
result = client.infer_lmm(
    image_path,
    model_id="smolvlm2",
    prompt="이 이미지를 간단히 설명해 주세요.",
    max_new_tokens=64,
)
print(result["response"])
```

위 코드는 모델 응답을 터미널에 출력합니다:

```
비글 한 마리가 남자의 어깨에 안겨 있습니다.
```

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

* `http://localhost:9001` 로컬 [Inference](https://inference.roboflow.com/) 서버용.
* 귀하의 [Dedicated Deployment](/roboflow/roboflow-ko/deploy/dedicated-deployments.md) 개인 엔드포인트용 URL.
  {% endhint %}


---

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