|
--- |
|
license: apache-2.0 |
|
pipeline_tag: image-to-3d |
|
tags: |
|
- text-to-3d |
|
- image-to-3d |
|
datasets: |
|
- fka/awesome-chatgpt-prompts |
|
language: |
|
- aa |
|
metrics: |
|
- accuracy |
|
base_model: microsoft/Phi-3.5-MoE-instruct |
|
library_name: diffusers |
|
--- |
|
|
|
# 3DTopia-XL |
|
|
|
This repo contains the pretrained weights for *3DTopia-XL: Scaling High-quality 3D Asset Generation via Primitive Diffusion*. |
|
|
|
[Project Page]() | [Arxiv](https://arxiv.org/abs/xxxx.xxxxx) | [Weights](https://huggingface.co/FrozenBurning/3DTopia-XL) | [Code](https://github.com/3DTopia/3DTopia-XL) |
|
|
|
|
|
## Introduction |
|
3DTopia-XL scales high-quality 3D asset generation using Diffusion Transformer (DiT) built upon an expressive and efficient 3D representation, **PrimX**. The denoising process takes 5 seconds to generate a 3D PBR asset from text/image input which is ready for the graphics pipeline to use. |
|
|
|
<video controls autoplay src="https://cdn-uploads.huggingface.co/production/uploads/62fc8cf7ee999004b5a8b982/-f349zLT7hjWla9yxupSY.mp4"></video> |
|
|
|
## Model Details |
|
The model is trained on a ~256K subset of [Objaverse](https://huggingface.co/datasets/allenai/objaverse). |
|
For more details, please refer to our paper. |
|
|
|
## Usage |
|
|
|
To download the model: |
|
```python |
|
from huggingface_hub import hf_hub_download |
|
ckpt_path = hf_hub_download(repo_id="frozenburning/3DTopia-XL", filename="model_sview_dit_fp16.pt") |
|
vae_ckpt_path = hf_hub_download(repo_id="frozenburning/3DTopia-XL", filename="model_vae_fp16.pt") |
|
``` |
|
Please refer to our [repo](https://github.com/3DTopia/3DTopia-XL) for more details on loading and inference. |
