> 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/paligemma2.md).

# PaliGemma 2

PaliGemma 2는 Google의 비전-언어 모델입니다. 이미지를 입력과 텍스트 프롬프트를 받아 텍스트 응답을 반환합니다. 우리는 우리의 [Serverless Hosted API](/roboflow/roboflow-ko/deploy/serverless-hosted-api-v2.md), [Dedicated Deployments](/roboflow/roboflow-ko/deploy/dedicated-deployments.md)그리고 [자체 호스팅 Inference](https://inference.roboflow.com/).

## 코드 샘플

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

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

다음 값을 전달하세요 [Roboflow API Key](https://app.roboflow.com/settings/api) 를 `API_KEY` 환경 변수입니다. 샘플은 사전 학습된 `paligemma2-3b-pt-224` 캡션 프롬프트가 포함된 체크포인트.

```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"),
)
result = client.infer_lmm(
    image_path,
    model_id="paligemma2-3b-pt-224",
    prompt="caption en",
    max_new_tokens=64,
)
print(result["response"])
```

위 코드는 모델 응답을 터미널에 출력합니다:

```
그 사람은 진정한 개 애호가입니다 .
```

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

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

Roboflow에서 자신만의 PaliGemma 2 체크포인트를 학습하고 해당 `workspace/project/version` 식별자를 사용합니다. 다음을 참조하세요. [Inference 문서](https://inference.roboflow.com/) 추가 프롬프트 형식 및 지원되는 체크포인트를 확인하세요.


---

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