---
title: consistency-models-test
canonical_url: "https://www.modelscope.cn/models/hf-diffusers/consistency-models-test"
md_url: "https://www.modelscope.cn/models/hf-diffusers/consistency-models-test.md"
repository: hf-diffusers/consistency-models-test
last_updated: 2024-11-07
license: mit
parameters: 2.4M
tensor_type:
  - F32
library_name:
  - safetensors
  - diffusers
  - pytorch
frameworks:
  - pytorch
downloads: 1820
stars: 0
---

# consistency-models-test

> consistency-models-test - hf-diffusers 在 ModelScope 开源的模型。These UNet2DModel checkpoints are small randomly-initialized U-Nets which accept 32x32 images for use in testing consistency models. "testunetclasscond" is class-conditional (e.g. contains a class…

hf-diffusers/consistency-models-test 是 ModelScope 魔搭社区上的 2.4M 参数机器学习模型，采用 mit 许可。

- **Repository**: hf-diffusers/consistency-models-test
- **License**: mit
- **Parameters**: 2.4M
- **Downloads**: 1820
- **Stars**: 0
- **Last updated**: 2024-11-07

Source: https://www.modelscope.cn/models/hf-diffusers/consistency-models-test

---

These `UNet2DModel` checkpoints are small randomly-initialized U-Nets which accept 32x32 images for use in testing consistency models.
"test_unet_class_cond" is class-conditional (e.g. contains a class label embedding), while "test_unet" is not.
Please refer to the [original model card](https://github.com/openai/consistency_models/blob/main/model-card.md) for more information about consistency models.