Instructions to use TencentARC/OREO with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Trellis
How to use TencentARC/OREO 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
Add oreo_v1 checkpoint (checkpoint_10_3157)
Browse files- README.md +25 -0
- oreo_v1/model.safetensors +3 -0
- oreo_v1/model_1.safetensors +3 -0
README.md
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---
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license: mit
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library_name: pytorch
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tags:
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- 3d
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- oreo
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- rendering
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- editing
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- trellis
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pipeline_tag: other
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---
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# OREO
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Checkpoints for **OREO (Rendering-Editing-Optimization)**.
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## Checkpoints
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- [`oreo_v1/`](oreo_v1): from training run `trellis-dual-contrast-flowedit-8gpu`, `checkpoint_10_3157` (global step 3157)
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- `model.safetensors`
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- `model_1.safetensors`
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## Code
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- GitHub: https://github.com/TencentARC/OREO-RenderingEdittingOptimization
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oreo_v1/model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:ee4ab6fb85fe0e0f91814d07c23a5e185ddc0510c1eef1a51695ef338e4a2153
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size 1203755168
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oreo_v1/model_1.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:8d771836807eff1a919af6576e46f456986c21adf4412bb65ad1a97fcea210d8
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size 1130770872
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