Downloads · 30 days
0
llama2thedog/BIM-JEPA-FM-hf
BIM-JEPA-FM-hf is a feature extraction model from llama2thedog. Use it when you need embeddings to search or compare text. It is set up for pytorch. The card lists the license as mit.
BIM-JEPA-FM fine-tuned for 20-way IFCNetCore object classification. Provided for the inference demo.
Downloads · 30 days
0
Access
Public
Updated Aug 8, 2026
Repo size
269 MB
Likes
0
Public
Click a slice to open those files.
.ckpt269 MB · 100%
From the Hugging Face model README
BIM-JEPA-FM fine-tuned for 20-way IFCNetCore object classification. Provided for the inference demo.
| File | checkpoints/bim-jepa-fm-ifcnetcore.ckpt |
| Task | IFCNetCore classification, 20 classes |
| Backbone | 12-layer transformer, 384 dim, 6 heads |
| Head | MLP, 256 dim, mean+max pooling |
| Fine-tuning | 350 epochs from the BIM-JEPA-FM pre-trained encoder |
from huggingface_hub import hf_hub_download
hf_hub_download(
"llama2thedog/BIM-JEPA-FM-hf",
"checkpoints/bim-jepa-fm-ifcnetcore.ckpt",
local_dir="/content/",
)
The demo notebook loads this checkpoint through BimJepaClassification; the two model
families are architecturally identical, so only the checkpoint path differs.
@article{shi2026toward,
title={Toward generalizable foundation models for 3D BIM geometry using a joint embedding predictive architecture},
author={Shi, Jack Wei Lun and Solihin, Wawan and Weng, Yufeng and Liang, Houhao and Zhao, Yimin and Poh, Leong Hien and Yeoh, Justin K.W.},
journal={Automation in Construction},
volume={191},
pages={107169},
year={2026},
publisher={Elsevier}
}