All credit to the original authors (Damo XR Lab /
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
,
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
import json, struct
withopen("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__"])) # 1523print(len([k for k in header if k.startswith("shape_head.")])) # 41
Runs of federicoramos77 LHMPP-700M-PixelShuffle on huggingface.co
24
Total runs
1
24-hour runs
0
3-day runs
3
7-day runs
-9
30-day runs
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