| --- |
| library_name: transformers |
| pipeline_tag: text-generation |
| tags: |
| - genomics |
| - dna |
| - generative |
| - ntv3 |
| - enhancer-generation |
| - mdlm |
| - diffusion |
| - conditional-generation |
| license: other |
| language: |
| - code |
| model_parameter_count: 658672910 |
| --- |
| |
|
|
| ## 🧬 NTv3: A Foundation Model for Genomics |
|
|
| NTv3 is a series of foundational models designed to understand and generate genomic sequences. It unifies representation learning, functional prediction, and controllable sequence generation within a single, efficient U-Net-like architecture. It also enables the modeling of long-range dependencies, up to 1 Mb of context, at nucleotide resolution. Pretrained on 9 trillion base pairs, NTv3 excels at functional-track prediction and genome annotation across 24 animal and plant species. It can also be fine-tuned into a controllable generative model for genomic sequence design. This is the **generative model** based on NTv3, capable of context-aware DNA sequence generation with desired activity levels.It builds on the post-trained NTv3 model with MDLM based fine-tuning.For more details, please refer to the [NTv3 paper](https://www.biorxiv.org/content/10.64898/2025.12.22.695963v1). |
|
|
| ## ⚖️ License Summary |
|
|
| 1. The Licensed Models are **only** available under this License for Non-Commercial Purposes. |
| 2. You are permitted to reproduce, publish, share and adapt the Output generated by the Licensed Model only for Non-Commercial Purposes and in accordance with this License. |
| 3. You may **not** use the Licensed Models or any of its Outputs in connection with: |
| 1. any Commercial Purposes, unless agreed by Us under a separate licence; |
| 2. to train, improve or otherwise influence the functionality or performance of any other third-party derivative model that is commercial or intended for a Commercial Purpose and is similar to the Licensed Models; |
| 3. to create models distilled or derived from the Outputs of the Licensed Models, unless such models are for Non-Commercial Purposes and open-sourced under the same license as the Licensed Models; or |
| 4. in violation of any applicable laws and regulations. |
|
|
| ## 📋 Model Summary |
|
|
| - Architecture: Conditioned U-Net with adaptive layer norms + Transformer stack |
| - Training: Masked Discrete Language Modeling (MDLM) |
| - Conditioning: Species + Activity levels (0-4) |
| - Tokenizer: Character-level over A T C G N + special tokens |
| - Dependencies: transformers >= 4.55.0 |
| - Input size: Model trained on 4096bp sequences with 249bp generation length |
| - Note: Custom code → use `trust_remote_code=True` |
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|
