Geneformer V1 10M
Geneformer is a single-cell transcriptome foundation model designed to learn gene-network context from many human single-cell transcriptomes.
What it does
Geneformer can produce cell representations and supports downstream workflows such as cell or gene classification, embedding extraction, and in-silico perturbation analysis.
Current status in Liatir
Geneformer V1 10M is installable as a signed Runtime Box. Liatir pins the official V1 checkpoint and matching Genecorpus-30M dictionaries to one upstream revision instead of following the repository's changing default model.
Expected inputs
- Human AnnData
.h5addata with non-negative raw counts in.X. - Ensembl gene IDs in
var["ensembl_id"], or Ensembl IDs asvar_names. - Optional
obs["n_counts"]; Liatir computes totals from.Xwhen absent. - Optional
obs["filter_pass"]to include only passing cells.
Expected outputs
- Embedded AnnData with
obsm["X_geneformer"]. - Lightweight CSV preview and JSON summary.
- Input warnings, metrics, Jobs, Results, and reproducible provenance.
The current Liatir slice produces cell embeddings only. Gene-network inference, classification, fine-tuning, and in-silico perturbation are not exposed by this runtime.
Hardware and installation
Measured CPU throughput was not viable for the current product target. The published native targets are macOS arm64 Metal, Linux x86_64 CUDA 12.9 and Windows x86_64 CUDA 12.8. Liatir does not substitute a CPU or different CUDA target when one of these exact environments is unavailable.
The input matrix is normalized per cell to 10,000 counts, scaled by the official Genecorpus-30M gene medians, converted to the V1 rank-value encoding, and capped at 2,048 gene tokens. Cell embeddings are mean-pooled from the second-to-last hidden layer. The original input file is never modified.