microsoft / microsoft/TRELLIS.2
Is the pretrain weight of sparse structure vae open sourced?
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- Python
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Description
parser.add_argument('--resolution', type=int, default=64,
help='Sparse voxel resolution')
parser.add_argument('--shape_latent_name', type=str, default=None,
help='Name of the shape latent files')
parser.add_argument('--enc_pretrained', type=str, default='microsoft/TRELLIS-image-large/ckpts/ss_enc_conv3d_16l8_fp16',
help='Pretrained encoder model')
parser.add_argument('--model_root', type=str,
help='Root directory of models')
Where is 'microsoft/TRELLIS-image-large/ckpts/ss_enc_conv3d_16l8_fp16
Contributor guide
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First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by searching the repository documentation and model-loading entry points for the --enc_pretrained argument and its default path, microsoft/TRELLIS-image-large/ckpts/ss_enc_conv3d_16l8_fp16. Done means confirming whether these sparse structure VAE weights are available and documenting their source or availability clearly.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Documentation
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100