# Obtain AceFF NNP models

**You will learn:** how to download an AceFF neural-network checkpoint manually, for offline use or version pinning.

**Prerequisites:**

- ACEMD installed with NNP support.

AceFF is the family of neural-network potentials developed by Acellera. The current release is **[AceFF 2.0](https://huggingface.co/Acellera/AceFF-2.0)**, distributed under the Apache 2.0 license — no HuggingFace account, no access request, no token needed.

```{note}
For most users, the easiest path is to let ACEMD download and cache the model automatically — just set `nnp.name: AceFF-2.0` in your `input.yaml` and skip this page. See [Run an NNP/MM simulation](run-an-nnp-mm-simulation.md) or [Run a pure NNP simulation](run-a-pure-nnp-simulation.md).

This page covers the manual flow for offline machines, version pinning, or sharing a checkpoint across a cluster.
```

## Download

Pull the checkpoint directly:

```bash
curl -L -o aceff_v2.0.ckpt https://huggingface.co/Acellera/AceFF-2.0/resolve/main/aceff_v2.0.ckpt
```

Reference the resulting file from your `input.yaml` with `nnp.name: TorchMD-Net` and an explicit `nnp.file`:

```{code-block} yaml
:caption: input.yaml

nnp:
  file: aceff_v2.0.ckpt
  name: TorchMD-Net
  type: torch
```

## What AceFF 2.0 supports

- **Elements:** H, B, C, N, O, F, Si, P, S, Cl, Br, I.
- **Total charge:** -2, -1, 0, +1, +2.
- **Recommended timestep:** 2 fs (with hydrogen-mass repartitioning).
- **Architecture:** TensorNet v2 inside the TorchMD-Net runtime.

## Gotchas

```{warning}
**Small molecules only.** AceFF 2.0 is trained on a curated PubChem dataset of small molecules. Proteins, water, and other biomolecular polymers are **not** in the training set — applying AceFF 2.0 to those species (in either pure NNP or as the NNP region of an NNP/MM run) will give wrong forces. For NNP/MM, restrict `nnp.sel` to a single small-molecule ligand or cofactor.
```

```{warning}
Total charges outside the `-2…+2` range are not supported. Charged species at the edge of this range can still extrapolate poorly — if you see crashes, drop the timestep to 1 fs or fall back to an NNP/MM run with a smaller NNP region.
```

## See also

- [Run an NNP/MM simulation](run-an-nnp-mm-simulation.md)
- [Run a pure NNP simulation](run-a-pure-nnp-simulation.md)
- [NNP and NNP/MM concepts](../explanation/nnp-and-nnp-mm.md)