Waypoint: Outpost Bio's Open Microbiome Foundation Models
Overview
Outpost Bio open-sourced three artefacts under Apache 2.0, described in Treloar et al., bioRxiv 2026.05.02.722381:
| Artefact | What it is | Hugging Face |
|---|---|---|
| Waypoint | GPT-2-style causal LMs over taxonomic tokens, 6M–170M params | outpost-bio/Waypoint-6m, -45m, -170m |
| Atlas | 539,308 microbiome samples scraped from MGnify (485,377 pretrain / 53,931 benchmark) | outpost-bio/Atlas |
| Compass | Eight downstream tasks over four studies | outpost-bio/Compass |
The unifying idea: a microbiome sample is a sentence. Each taxon is one token, tokens are ordered by descending abundance z-score, and the model is trained with next-token prediction. A pretrained checkpoint then supplies sample-level embeddings or a fine-tuning backbone for prediction tasks.
All of it is driven by one CLI, waypoint, with five subcommands: prepare-dataset, embed,
finetune, benchmark, pretrain.
When to use
- Embedding 16S/shotgun taxonomic profiles into fixed-size vectors for clustering, visualisation, or a do…
