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https://github.com/nvidia/bionemo-framework
BioNeMo Framework: For building and adapting AI models in drug discovery at scale
https://github.com/nvidia/bionemo-framework
drug-discovery gpu machine-learning pytorch
Last synced: 4 days ago
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BioNeMo Framework: For building and adapting AI models in drug discovery at scale
- Host: GitHub
- URL: https://github.com/nvidia/bionemo-framework
- Owner: NVIDIA
- License: other
- Created: 2023-10-16T01:31:06.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-02-07T22:16:39.000Z (4 days ago)
- Last Synced: 2025-02-08T06:07:12.120Z (4 days ago)
- Topics: drug-discovery, gpu, machine-learning, pytorch
- Language: Jupyter Notebook
- Homepage: https://nvidia.github.io/bionemo-framework/
- Size: 223 MB
- Stars: 279
- Watchers: 40
- Forks: 35
- Open Issues: 75
-
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE/license.txt
- Codeowners: CODEOWNERS
- Security: SECURITY.md
Awesome Lists containing this project
README
# BioNeMo Framework
[](https://console.brev.dev/launchable/deploy/now?launchableID=env-2pPDA4sJyTuFf3KsCv5KWRbuVlU)
[](https://nvidia.github.io/bionemo-framework)
[](https://github.com/NVIDIA/bionemo-framework/actions/workflows/unit-tests.yml)
[](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/clara/containers/bionemo-framework/tags)
[](https://codecov.io/gh/NVIDIA/bionemo-framework)
NVIDIA BioNeMo Framework is a is a comprehensive suite of programming tools, libraries, and models designed for computational drug discovery.
It accelerates the most time-consuming and costly stages of building and adapting biomolecular AI models by providing
domain-specific, optimized models and tooling that are easily integrated into GPU-based computational resources for the
fastest performance on the market. You can access BioNeMo Framework as a free community resource here in this repository
or learn more at about getting an enterprise license for improved
expert-level support.
## Structure of the Framework
The `bionemo-framework` is organized into independently installable namespace packages. These are located under the
`sub-packages/` directory. Please refer to [PEP 420 – Implicit Namespace Packages](https://peps.python.org/pep-0420/)
for details.
## Documentation Resources
- **Official Documentation:** For user guides, API references, and troubleshooting, visit our [official documentation](https://docs.nvidia.com/bionemo-framework/latest/).
- **In-Progress Documentation:** To explore the latest features and developments, check the documentation reflecting the current state of the `main` branch [here](https://nvidia.github.io/bionemo-framework/). Note that this may include references to features or APIs that are not yet finalized.
## Getting Started with BioNeMo Framework
Full documentation on using the BioNeMo Framework is provided in our documentation:
. To simplify the integration of optimized third-party dependencies, BioNeMo is primarily distributed as a containerized library. You can download the latest released container for the BioNeMo Framework from
[NGC](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/clara/containers/bionemo-framework). To launch a pre-built container, you can use the brev.dev launchable [](https://console.brev.dev/launchable/deploy/now?launchableID=env-2pPDA4sJyTuFf3KsCv5KWRbuVlU) or execute the following command:
```bash
docker run --rm -it \
--gpus=all --ipc=host --ulimit memlock=-1 --ulimit stack=67108864 \
nvcr.io/nvidia/clara/bionemo-framework:nightly \
/bin/bash
```
### Setting up a local development environment
#### Initializing 3rd-party dependencies as git submodules
The NeMo and Megatron-LM dependencies are included as git submodules in bionemo2. The pinned commits for these submodules represent the "last-known-good" versions of these packages
that are confirmed to be working with bionemo2 (and those that are tested in CI).
To initialize these sub-modules when cloning the repo, add the `--recursive` flag to the git clone command:
```bash
git clone --recursive [email protected]:NVIDIA/bionemo-framework.git
cd bionemo-framework
```
To download the pinned versions of these submodules within an existing git repository, run
```bash
git submodule update --init --recursive
```
Different branches of the repo can have different pinned versions of these third-party submodules. Ensure submodules are automatically updated after switching branches or pulling updates by configuring git with:
```bash
git config submodule.recurse true
```
**NOTE**: this setting will not download **new** or remove **old** submodules with the branch's changes.
You will have to run the full `git submodule update --init --recursive` command in these situations.
#### Build the Docker Image Locally
With a locally cloned repository and initialized submodules, build the BioNeMo container using:
```bash
docker buildx build . -t my-container-tag
```
#### VSCode Devcontainer for Interactive Debugging
We distribute a [development container](https://devcontainers.github.io/) configuration for vscode
(`.devcontainer/devcontainer.json`) that simplifies the process of local testing and development. Opening the
bionemo-framework folder with VSCode should prompt you to re-open the folder inside the devcontainer environment.
> [!NOTE]
> The first time you launch the devcontainer, it may take a long time to build the image. Building the image locally
> (using the command shown above) will ensure that most of the layers are present in the local docker cache.
### Quick Start
See the [tutorials pages](https://docs.nvidia.com/bionemo-framework/latest/user-guide/examples/bionemo-esm2/pretrain/)
for example applications and getting started guides.