SciCore-Omics

About

What SciCore-Omics is

🧬 SciCore-Omics A tri-modal foundation model unifying histology, spatial transcriptomics, and biological language [](https://huggingface.co/openbmb/SciCore-Omics) [](https://github.com/OpenBMB/Scicore-Omics) [](https://huggingface.co/spaces/Alkaidxxy/SciCore-Omics) [](https://github.com/OpenBMB/Scicore-Omics/blob/main/LICENSE) 🔍 Overview SciCore-Omics is a tri-modal biomedical foundation model that connects histology images, spatial transcriptomic profiles, and biological language for spatial biology and pathology-related reasoning. The model introduces a gene-aware branch based on NicheFormer + Gene Q-Former + Gene Projector, enabling transcriptomic information to be aligned with the language-model token space. SciCore-Omics supports: 🖼️ image-only reasoning; 🧬 gene-only reasoning; 🖼️🧬 joint image-gene reasoning; 💬 natural-language biomedical interpretation. ✨ Highlights Tri-modal modeling of histology, spatial transcriptomics, and language Gene-aware transcriptomic encoding with NicheFormer Unified image-gene-text reasoning in the language-model space Designed for spatial biology, pathology reasoning, and biomedical interpretation Open-source model weights, code, and demo 🚀 Quick Start This Hugging Face repository hosts the model weights. For full inference and training code, please refer to the GitHub repository: Download the model weights: Minimal loading example: For complete examples, please see: https://github.com/OpenBMB/Scicore-Omics/tree/main/eval 📦 Resources ⚠️ Limitations SciCore-Omics is released for research use only. It may generate inaccurate or incomplete biomedical interpretations and should not be used as a standalone clinical diagnostic or treatment recommendation system. 📚 Citation 📄 License This project is released under the Apache-2.0 License.

Summarised from the published model card. Read the full card on the HuggingFace links below.

Specifications

What it is

How it works

How embedding models work

Variants

Sizes & precisions

Open weights ship in several sizes and precisions. One page, all the variants — pick the one that fits your GPU. VRAM figures are estimates from model size.

Using it via the API

Call it like any OpenAI endpoint

Once AxForge deploys scicore-omics for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (scicore-omics below is illustrative; you get the exact model name on deployment.)

$ curl -sS https://api.axforge.ai/v1/embeddings \
  -H "Authorization: Bearer $AXFORGE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"scicore-omics","input":"text to embed"}'

Details

Languages, data & research

Licence

Open weights

Sources

Weights & code

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