ailab-bio/TACK-Context-Encoding
PCA-reduced context embedding tables for the tackai fusion surrogates (tackai.fusion):
one lookup table plus a PCA side-file per block (assay (8-d), cell (47-d), e3 (7-d), poi (51-d)), and manifest.json recording
each file's sha256, byte size and dimensions. Published from a protein_space="combined" encoder; from_pretrained reproduces that by default.
These tables are inputs to every fusion model, never the output of one — a fitted ensemble is only meaningful against the exact tables it was built with, so this repo is versioned by commit rather than by file content.
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from tackai.fusion.data import FusionData
data = FusionData.from_pretrained("ailab-bio/TACK-Context-Encoding")
context = data.encode_context({"poi_seq": ..., "e3_seq": ..., "cell_id": ..., "assay": ...})
from_pretrained installs these files into TACKAI_CACHE and verifies them against this
repo's manifest.json before use.
Generated by tackai.fusion.context.stage_context_tables (tackai version
1.0.0) — do not hand-edit; re-stage and re-upload instead.