CELL-FM
Model checkpoints for CELL-FM, a flow-matching model that generates cell microscopy images from protein sequence.
One subfolder per model family. Point a loader at the subfolder it needs; the
demo code does this through CELLFM_MODEL_REPO + a path prefix.
condenseq/ — sequence-conditioned condensate imaging
Trained on CondenSeq, 160x160 GFP images. Drives the condensate titration demo: sequence in, condensate-probability curve out, integrated into AUC and AAC.
| File | Model | Source checkpoint |
|---|---|---|
condenseq/cellfm_seq2img.bin |
CELL-FM CS sequence-to-image generator, ESM-C 600M encoder included (745 M params) | pretrain_condenseq/cellfm_seq2img/checkpoint-50000 |
condenseq/vae.bin |
Image VAE, 160x160, 3 down blocks, 4 latent channels | pretrain_condenseq/vae/checkpoint-50000 |
condenseq/vit_cls.bin |
ViT condensed/diffuse classifier, 2-channel 160x160 input (26 M params) | PT_CondenSeq_img_ViT_cls_R1/checkpoint-10000 |
Hyperparameters mirror scripts/cell_fm_cs/evaluate_seq2img.sh and
scripts/vit_cls_condenseq_img/pretrain.sh in the CELL-FM repository, and are set
in huggingface_space/pipeline.py there.
Reference values at 512 images / 100 ODE steps / seed 6: NUP98 WT gives AUC 0.4896 and AAC 0.0001; its 1F->S mutant gives AUC 0.4561.
Adding a model family
Upload under a new prefix (hpa/, opencell_3d/, ...) and add a section here.
upload_weights.py in the demo takes a {path_in_repo: local_checkpoint} map, so
new families need only a new entry.