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# twelvelabs-marengo3.0

An enhanced multimodal embedding model that extends the capabilities of Marengo 2.7 with support for text and image interleaved input modality. This model generates high-quality vector representations of video, text, audio, image, and interleaved text-image content for similarity search, clustering, and other machine learning tasks.

**Details**

- Model name: `twelvelabs-marengo3.0`
- Model source: [https://www.twelvelabs.io](https://www.twelvelabs.io)
- Model author: Twelve Labs, Inc.
- Model license: [https://www.twelvelabs.io/legal/tos](https://www.twelvelabs.io/legal/tos)
- Exposes embeddings? yes
- Tags: `video, embeddings, official`

**Requirements**

- Packages: `twelvelabs>=1.2.8`
- CPU support
  - N/A
- GPU support
  - N/A

**Example usage**

```python
import fiftyone as fo
import fiftyone.zoo as foz
import fiftyone.brain as fob

dataset = foz.load_zoo_dataset("quickstart-video")

model = foz.load_zoo_model("twelvelabs-marengo3.0")

dataset.apply_model(model, label_field="predictions")

dataset.compute_embeddings(model, embeddings_field="twelvelabs")

# Text-to-video search
fob.compute_similarity(
    dataset,
    model=model,
    embeddings="twelvelabs",
    brain_key="tl_sim",
)

view = dataset.sort_by_similarity(
    "a person riding a bike",
    brain_key="tl_sim",
    k=10,
)

session = fo.launch_app(view)
```