# Qwen/Qwen2.5-VL-32B-Instruct
#### NOTE
This is a [remotely-sourced model](../remote.md#model-zoo-remote) from the
[qwen2_5_vl](../../plugins/plugins_ecosystem/qwen2_5_vl.html) plugin, maintained by the community.
It is not part of FiftyOne core and may have special installation requirements.
Please review the plugin documentation and license before use.
Qwen2.5-VL is the multimodal large language model series developed by Qwen team, Alibaba Cloud..
**Details**
- Model name: `Qwen/Qwen2.5-VL-32B-Instruct`
- Model source: [https://huggingface.co/Qwen/Qwen2.5-VL-32B-Instruct](https://huggingface.co/Qwen/Qwen2.5-VL-32B-Instruct)
- Model author: QwenLM
- Model license: Apache-2.0 license
- Exposes embeddings? no
- Tags: `detection, segmentation, ocr, VLM, zero-shot`
**Requirements**
- Packages: `huggingface-hub, transformers, torch, torchvision, qwen-vl-utils, accelerate`
- CPU support
- yes
- GPU support
- yes
**Example usage**
```python
import fiftyone as fo
import fiftyone.zoo as foz
foz.register_zoo_model_source("https://github.com/harpreetsahota204/qwen2_5_vl")
dataset = foz.load_zoo_dataset(
"coco-2017",
split="validation",
dataset_name=fo.get_default_dataset_name(),
max_samples=50,
shuffle=True,
)
model = foz.load_zoo_model("Qwen/Qwen2.5-VL-32B-Instruct")
dataset.apply_model(model, label_field="predictions")
session = fo.launch_app(dataset)
```