> 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/deployment/legacy/legacy-serverless/video-inference/use-a-fine-tuned-model.md).

# Use a Fine-Tuned Model

You can use models you have trained or uploaded to Roboflow with the video inference API.

### Use a Fine-Tuned Model with the Video Inference API

First, install the Roboflow Python package:

```bash
pip install roboflow
```

Next, create a new Python file and add the following code:

```python
from roboflow import Roboflow

rf = Roboflow(api_key="API_KEY")
project = rf.workspace().project("PROJECT_NAME")
model = project.version(MODEL_ID).models()[0]

job_id, signed_url, expire_time = model.predict_video(
    "football-video.mp4",
    fps=5,
    prediction_type="batch-video",
)

results = model.poll_until_video_results(job_id)

print(results)
```

Above, replace:

* `API_KEY`: with your Roboflow API key
* `PROJECT_NAME`: with your Roboflow project ID.
* `MODEL_ID`: with your Roboflow model ID.

*Important note: Currently Roboflow's video inference only supports models trained within Roboflow after June 30th, 2023. We are working toward including older models.*

[Learn how to retrieve your API key](https://docs.roboflow.com/reference/authentication/authentication/find-your-roboflow-api-key).

[Learn how to retrieve a model ID](https://docs.roboflow.com/reference/authentication/authentication/workspace-and-project-ids).