Instructions to use litert-community/Idol with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LiteRT
How to use litert-community/Idol with LiteRT:
# 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
Commit History
Today
-
Faster default form in the root; the first release's form moves to 262k/
Verified signatureTwo forms. The repo's root now holds a faster default form: a photo makes a splat of 65,536 Gaussians (2,048 anchors), every graph but BiRefNet runs on the GPU at FP16, the denoiser's joint blocks 1-22 share one graph (den_joint_mid.tflite, weights in den_joint_w.f32) and the Gaussian decoder's graphs 1-6 share another (gs_mid.tflite, weights in gs_w.f32); the app copies a block's weights in before each call, so each is compiled once per photo. The first release's form (262,144 Gaussians, a graph per block, GPU FP16 with fp32 accumulation) moves to 262k/ with its own manifest.json; its files are the same bytes as the root's at commit e7ee1226. On a Galaxy S26 the first photo after start on a cool phone took 158 s with the default form and 267 s with the 262k/ form. Four-view renders against the author's default on the phone (armchair / axolotl / succulent; threshold 25 dB): 34.41 / 32.26 / 34.26 dB PSNR with the default form, 46.59 / 42.34 / 41.43 dB with the 262k/ form.74728e5