---
license: apache-2.0
library_name: pytorch
pipeline_tag: image-to-3d
tags:
  - mirror
  - gaussian-splatting
  - lhm
---

# LHMPP-700M-PixelShuffle (mirror)

Unmodified mirror of [`Damo_XR_Lab/LHMPP-700M-PixelShuffle`](https://www.modelscope.cn/Damo_XR_Lab/LHMPP-700M-PixelShuffle)
from ModelScope, at revision `5f1c4274068e11b93721219618d36594b6087cb6`.

All credit to the original authors (Damo XR Lab / [LHM-plusplus](https://github.com/aigc3d/LHM-plusplus)).
Redistributed under Apache-2.0, the licence declared on the source repository.

## Why this mirror exists

ModelScope throughput from cloud datacenters in Europe/US measures around
**0.7 MiB/s**, so pulling the 4.87 GB `model.safetensors` takes upwards of three
hours — longer than a Hugging Face Space stage timeout allows, and the partial
download is discarded on failure. The same file over the HF CDN completes in
about a minute.

## Contents

| File | Size | Note |
| --- | --- | --- |
| `model.safetensors` | 4984.3 MiB | byte-identical to source (5226465708 bytes, 1523 tensors) |
| `config.json` | 3103 B | byte-identical to source |
| `configuration.json` | 44 B | byte-identical to source |
| `README.md` | — | **rewritten** for HF model-card metadata; source card was ModelScope-specific |

Only the model card differs from upstream. The weights and configs are unchanged.

## This is the PixelShuffle variant

Not interchangeable with [`3DAIGC/LHMPP-700M`](https://huggingface.co/3DAIGC/LHMPP-700M),
despite the similar name. This checkpoint carries 41 `shape_head.*` tensors and
`predict_shape_dim: 10` in its config, giving it an image-predicted shape head;
`3DAIGC/LHMPP-700M` has no `shape_head` and instead defines a `neural_renderer`
block that this one lacks. Loading one where the other is expected fails on a
state-dict mismatch.

## Verifying against the source

```python
import json, struct

with open("model.safetensors", "rb") as f:
    header = json.loads(f.read(struct.unpack("<Q", f.read(8))[0]))

print(len([k for k in header if k != "__metadata__"]))            # 1523
print(len([k for k in header if k.startswith("shape_head.")]))    # 41
```