---
title: adjoint_sampling
canonical_url: "https://www.modelscope.cn/models/facebook/adjoint_sampling"
md_url: "https://www.modelscope.cn/models/facebook/adjoint_sampling.md"
repository: facebook/adjoint_sampling
last_updated: 2025-05-20
license: cc-by-nc-4.0
library_name:
  - pytorch
frameworks:
  - pytorch
language:
  - en
downloads: 323
stars: 0
---

# adjoint_sampling

> adjoint_sampling - facebook 在 ModelScope 开源的模型。Adjoint Sampling: Highly Scalable Diffusion Samplers via Adjoint Matching

facebook/adjoint_sampling 是 ModelScope 魔搭社区上的机器学习模型，采用 cc-by-nc-4.0 许可。

- **Repository**: facebook/adjoint_sampling
- **License**: cc-by-nc-4.0
- **Downloads**: 323
- **Stars**: 0
- **Last updated**: 2025-05-20

Source: https://www.modelscope.cn/models/facebook/adjoint_sampling

---

# Adjoint Sampling: Highly Scalable Diffusion Samplers via Adjoint Matching

This repository contains the models for our [official code release](https://github.com/facebookresearch/adjoint_sampling).  
Additionally, it contains the specific [eSEN](https://arxiv.org/abs/2502.12147) checkpoint that we used to train those models.  

**[Arxiv](https://arxiv.org/abs/2504.11713) (Accepted in ICML 2025)**  
*Authors: _Aaron Havens, Benjamin Kurt Miller, Bing Yan, Carles Domingo-Enrich, Anuroop Sriram, Brandon Wood, Daniel Levine, Bin Hu, Brandon Amos, Brian Karrer, Xiang Fu, Guan-Horng Liu, Ricky T. Q. Chen_*
![image/png](https://cdn-uploads.huggingface.co/production/uploads/67cd3633d2fd0e9ec4cbb329/8J1MzaVvtHjv4e5AY-S8B.png)

### Download models
```python
from huggingface_hub import snapshot_download

snapshot_download(
    repo_id="facebook/adjoint_sampling",
    local_dir="models",
    allow_patterns=[
        "am/",
        "bmam/",
        "pretrain_for_bmam/",
        "torsion/",
        "esen_spice.pt",
    ],
)
```