---
title: test-load-tiny-stable-diffusion-pipe-smashed-pro
canonical_url: "https://www.modelscope.cn/models/PrunaAI/test-load-tiny-stable-diffusion-pipe-smashed-pro"
md_url: "https://www.modelscope.cn/models/PrunaAI/test-load-tiny-stable-diffusion-pipe-smashed-pro.md"
repository: PrunaAI/test-load-tiny-stable-diffusion-pipe-smashed-pro
last_updated: 2026-01-13
pipeline_tag: text-to-image-synthesis
tasks:
  - text-to-image-synthesis
parameters: 2.2M
tensor_type:
  - F32
library_name:
  - safetensors
  - diffusers
  - pytorch
frameworks:
  - pytorch
downloads: 26
stars: 0
tags:
  - pruna-ai
---

# test-load-tiny-stable-diffusion-pipe-smashed-pro

> test-load-tiny-stable-diffusion-pipe-smashed-pro - PrunaAI 在 ModelScope 开源的模型。Model Card for PrunaAI/test-load-tiny-stable-diffusion-pipe-smashed-pro

- **Repository**: PrunaAI/test-load-tiny-stable-diffusion-pipe-smashed-pro
- **Tasks**: text-to-image-synthesis
- **Parameters**: 2.2M
- **Tags**: pruna-ai
- **Downloads**: 26
- **Stars**: 0
- **Last updated**: 2026-01-13

Source: https://www.modelscope.cn/models/PrunaAI/test-load-tiny-stable-diffusion-pipe-smashed-pro

---

# Model Card for PrunaAI/test-load-tiny-stable-diffusion-pipe-smashed-pro

This model was created using the [pruna](https://github.com/PrunaAI/pruna) library. Pruna is a model optimization framework built for developers, enabling you to deliver more efficient models with minimal implementation overhead.

## Usage

First things first, you need to install the pruna library:

```bash
pip install pruna
```

You can [use the diffusers library to load the model](https://huggingface.co/PrunaAI/test-load-tiny-stable-diffusion-pipe-smashed-pro?library=diffusers) but this might not include all optimizations by default.

To ensure that all optimizations are applied, use the pruna library to load the model using the following code:

```python
from pruna import PrunaModel

loaded_model = PrunaModel.from_hub(
    "PrunaAI/test-load-tiny-stable-diffusion-pipe-smashed-pro"
)
```

After loading the model, you can use the inference methods of the original model. Take a look at the [documentation](https://pruna.readthedocs.io/en/latest/index.html) for more usage information.

## Smash Configuration

The compression configuration of the model is stored in the `smash_config.json` file, which describes the optimization methods that were applied to the model.

```bash
{
    "batcher": null,
    "cacher": null,
    "compiler": null,
    "distiller": null,
    "enhancer": null,
    "factorizer": null,
    "pruner": null,
    "quantizer": null,
    "recoverer": null,
    "batch_size": 1,
    "device": "cpu",
    "save_fns": [],
    "load_fns": [
        "diffusers"
    ],
    "reapply_after_load": {
        "factorizer": null,
        "pruner": null,
        "quantizer": null,
        "distiller": null,
        "cacher": null,
        "recoverer": null,
        "compiler": null,
        "batcher": null,
        "enhancer": null
    }
}
```

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