Instructions to use torch-pointcloud/point-bert-base.dvae.xumin-yu with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- torch-pointcloud
How to use torch-pointcloud/point-bert-base.dvae.xumin-yu with torch-pointcloud:
import torch_pointcloud as tp model = tp.create_model("point-bert-base.dvae.xumin-yu", pretrained=True) - Notebooks
- Google Colab
- Kaggle
File size: 524 Bytes
118fb2f | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 | {
"library_name": "torch-pointcloud",
"name": "point-bert-base.dvae.xumin-yu",
"task": "pretraining",
"hparams": {
"in_channels": 0,
"num_groups": 64,
"group_size": 32,
"encoder_dims": 256,
"token_local_channels": [
128,
256
],
"token_global_channels": [
512
],
"num_tokens": 8192,
"tokens_dims": 256,
"decoder_dims": 256
},
"input_keys": [
"x",
"pos",
"batch"
],
"dataset": "shapenet55",
"author": "xumin-yu",
"license": "MIT"
}
|