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# point-transformer-v3-nuscenes-torch

Point Transformer V3 backbone pretrained on nuScenes LiDAR semantic segmentation; produces embeddings for 3D point cloud samples.

**Details**

- Model name: `point-transformer-v3-nuscenes-torch`
- Model source: [https://github.com/Pointcept/PointTransformerV3](https://github.com/Pointcept/PointTransformerV3)
- Model author: Xiaoyang Wu, et al.
- Model license: MIT
- Model size: 528.83 MB
- Exposes embeddings? yes
- Tags: `embeddings, 3d, point-cloud, lidar, nuscenes, torch, transformer, official`

**Requirements**

- Packages: `torch, spconv-cu120, torch-scatter, timm, addict, open3d`
- CPU support
  - no
- GPU support
  - yes

**Example usage**

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

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("point-transformer-v3-nuscenes-torch")

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

session = fo.launch_app(dataset)
```