PALM soft-target epoch 8

This repository contains the final PALM soft-target overlap-aware checkpoint and optional ClinVar-trained pathogenicity heads.

Files

palm_soft_target_epoch8.pt
pathogenicity/random_split_fold_1.pt
pathogenicity/random_split_fold_2.pt
pathogenicity/random_split_fold_3.pt
pathogenicity/random_split_fold_4.pt
pathogenicity/random_split_fold_5.pt
interpro_classes.tsv
checkpoint_manifest.json

interpro_classes.tsv maps every output class to its InterPro entry:

head    class_index  interpro_id  interpro_type  name
domain  0            IPR000001    Domain         Kringle
site    0            IPR000035    Conserved_site Alkylbase DNA glycosidase, conserved site

class_index is 0-based and per head: domain indices run 0-17950, and site indices restart at 0 and run to 1382. The checkpoint itself carries the same accession-to-index maps as ipr2domain and ipr2site; this file adds the human-readable names.

The annotation checkpoint predicts four residue-level outputs:

• domain occurrence: none, one, or multiple;
• site occurrence: none, one, or multiple;
• InterPro domain classes; and
• InterPro site classes.

Overlapping domain/site labels use uniform soft targets over all true classes. The final model uses ESM2-150M, LoRA on the last four ESM layers, learned all-layer pooling, and a bidirectional LSTM residue encoder.

Use

Install the code from the PALM GitHub repository, then use the Hugging Face artifact reference directly:

from palm import PALMPredictor

predictor = PALMPredictor(
    "hf://Wangwpi/PALM::palm_soft_target_epoch8.pt",
    device="cuda",
)
annotation = predictor.annotate("MSEQUENCE...")

The checkpoint is downloaded from the Wangwpi/PALM model repository and cached by huggingface_hub.

Pathogenicity heads

The five random-split heads were selected at epochs 3, 4, 4, 3, and 4 using inner-validation AUROC within a common 15-epoch budget. Their final prediction is the unweighted arithmetic mean of the five pathogenicity probabilities.

These are supervised ClinVar-trained models. Their outputs must not be called zero-shot. PALM annotation/embedding WT-mutant disruption can be evaluated separately without loading these heads.

Limitations

• The annotation and pathogenicity models are research models, not clinical diagnostic tools.
• Variant results depend on the protein transcript supplied to the model.
• Long proteins are limited by the ESM2 context window; variant workflows crop around the amino-acid change.
• Cohort filters and transcript aggregation must be reported with benchmark results.

License

Released under the MIT license, the same terms as the GitHub repository (https://github.com/WGLab/PALM).

PALM is a fine-tune of facebook/esm2_t30_150M_UR50D, which is itself MIT licensed. The annotation model was trained on UniRef50 sequences labelled with InterPro domain and site entries, and the optional pathogenicity heads on ClinVar variant classifications; anyone redistributing derived data should check the terms of those sources as well.

Citation

Citation information will be added when the PALM manuscript is available.