metadata
library_name: cellpose
pipeline_tag: image-segmentation
base_model: mouseland/cellpose-sam
base_model_relation: quantized
license: bsd-3-clause
arXiv: 2609.21038
tags:
- cellpose
- cellpose-sam
- microscopy
- quantization
- image-segmentation
Cellpose-SAM WQuant — W8A16
Ready-to-load W8A16 quantized variant of
Cellpose-SAM cpsam_v2.
Load
import runpy
from huggingface_hub import hf_hub_download
loader = runpy.run_path(
hf_hub_download("capicu-ai/cellpose-sam-wquant-w8a16", "runtime_loader.py")
)
model = loader["load_model"]()
Pass device="cuda" to load_model for CUDA.
Result
- Weight size: 295.8 MiB
- Compression versus FP32: 3.93x
- Evaluated paired samples: 20
- Complete bounded-panel criterion met: Yes
- Reload verification normalized RMSE: 0.0
results.json and model_registry.json contain the compact machine-readable
record.
Citation
If you use this model or code, please cite our paper:
@article{cruzromero2026retention,
title={Retention-Constrained Post-Training Quantization of Cellpose-SAM for Stem Cell Microscopy},
author={Cruz Romero, Sebasti{\'a}n A.},
journal={arXiv preprint arXiv:2609.21038},
note={Accepted at NeurIPS 2026 LXAI Workshop},
year={2026}
}