Instructions to use overyonder/espalier-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Trellis
How to use overyonder/espalier-2 with Trellis:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
over|yonder Espalier-2
over|yonder Espalier-2 runs Microsoft's TRELLIS.2-4B at its highest resolution, the 1536 cascade, on a 16 GB consumer GPU. It uses Microsoft's weights unchanged, so this repository holds no weights of its own. The code, patches and install script are on GitHub.
An espalier is a fruit tree trained flat against a trellis, so a full-size tree grows in a narrow space.
Microsoft lists a 24 GB GPU as the minimum, and on a 16 GB card its 1536 pipeline runs out of memory in the shape decoder and again in the GLB export. Espalier-2 tiles the decoders' two highest-resolution stages, runs the export's remesh in chunks, and keeps data the export doesn't need off the GPU. On an RTX 5070 Ti, generating the catapult above peaked at 11.9 GiB and its export at 13.3 GiB, measured from the NVIDIA driver.
The article over|yonder Espalier-2: TRELLIS.2 at 1536 on a 16 GB GPU explains every change and measurement.
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