🧬 Evo-2 40B (BioNeMo) — Fine-tuned for Hepatocellular Carcinoma (HCC)
Model Name: evo2-7b-bionemo-hcc-mouse
Base Model: Evo-2 40B (Arc Institute × NVIDIA)
Framework: NVIDIA BioNeMo / NeMo2 (Megatron-LM backend)
Fine-tuning Domain: Hepatocellular Carcinoma (HCC)
Organism: Mus musculus (GRCm39)
Chromosomes Used: 1, 4, 6, 7, 8, 9, 11, 12, 17
Context: Developed by the Brilliant team for the EuroCC AI Hackathon 2025
🧠 Overview
This repository contains a fine-tuned checkpoint of the Evo-2 40B biomolecular foundation model, adapted to explore sequence patterns linked to Hepatocellular Carcinoma (HCC) using curated Mus musculus genomic data.
Training leveraged the NVIDIA BioNeMo framework on multi-GPU H100 infrastructure during the EuroCC AI Hackathon 2025, focusing on genome-scale representation learning and mutation-impact analysis in cancer-related regions.
⚙️ Fine-tuning Dataset
| Property | Description |
|---|---|
| Source organism | Mus musculus |
| Genome build | GRCm39 |
| Chromosomes | 1, 4, 6, 7, 8, 9, 11, 12, 17 |
| Data type | DNA sequences (FASTA) |
| Task | Representation learning and sequence modeling for HCC pathways |
| Preprocessing | Standard BioNeMo Evo-2 pipeline (tokenization, masking, packing) |
🚀 Training Setup
| Parameter | Value |
|---|---|
| Base model | Evo-2 40B base |
| Framework | NVIDIA BioNeMo / NeMo2 |
| Precision | BF16 |
| GPUs | 16 × NVIDIA H100 |
| Tensor Parallel (TP) | 16 |
| Pipeline Parallel (PP) | 1 |
| Context Parallel (CP) | 1 |
| Micro-batch size | Tuned for memory efficiency |
| Dataset split | 90 % train / 5 % val / 5 % test |
🧩 Usage
python train_evo2.py model.restore_from_path=./checkpoint model.tensor_parallel_size=4 model.pipeline_model_parallel_size=2 trainer.precision=bf16
🧬 Background
Evo-2
A genomic and protein language model jointly developed by Arc Institute and NVIDIA, trained on nearly 9 trillion biological tokens across many species and capable of context lengths up to 1 million tokens.
BioNeMo
NVIDIA’s AI platform for biomolecular modeling, built on NeMo 2 + Megatron-LM for scalable multi-GPU training and fine-tuning.
EuroCC AI Hackathon 2025
Collaborative event (14–23 October 2025) promoting AI/HPC innovation, organized by EuroCC National Competence Centres in partnership with NVIDIA and OpenACC.
📜 License & Citation
This repository and checkpoint are released for research and educational use under the same terms as the original Evo-2 and BioNeMo frameworks (see LICENSE).
⚠️ Notes & Limitations
This fine-tuned version is experimental, trained on selected Mus musculus chromosomes related to HCC pathways.
It is not intended for clinical or diagnostic use. Users must apply appropriate bioethical and biosafety standards in downstream applications.
💡 Acknowledgements
Special thanks to the EuroCC AI Hackathon mentors and NVIDIA BioNeMo team for guidance and compute resources, and to the Arc Institute for releasing the original Evo-2 foundation models.