---
title: test-save-tiny-stable-diffusion-pipe-smashed-pro
canonical_url: "https://www.modelscope.cn/models/PrunaAI/test-save-tiny-stable-diffusion-pipe-smashed-pro"
md_url: "https://www.modelscope.cn/models/PrunaAI/test-save-tiny-stable-diffusion-pipe-smashed-pro.md"
repository: PrunaAI/test-save-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: 32
stars: 0
tags:
  - safetensors
  - pruna-ai
  - pruna_pro-ai
---

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

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

- **Repository**: PrunaAI/test-save-tiny-stable-diffusion-pipe-smashed-pro
- **Tasks**: text-to-image-synthesis
- **Parameters**: 2.2M
- **Tags**: safetensors, pruna-ai, pruna_pro-ai
- **Downloads**: 32
- **Stars**: 0
- **Last updated**: 2026-01-13

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

---

# Model Card for PrunaAI/test-save-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_pro
```

You can [use the diffusers library to load the model](https://huggingface.co/PrunaAI/test-save-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_pro import PrunaProModel

loaded_model = PrunaProModel.from_pretrained(
    "PrunaAI/test-save-tiny-stable-diffusion-pipe-smashed-pro"
)
# we can then run inference using the methods supported by the base model
```


For inference, you can use the inference methods of the original model like shown in [the original model card](https://huggingface.co/hf-internal-testing/tiny-stable-diffusion-pipe?library=diffusers).
 Alternatively, you can visit [the Pruna documentation](https://docs.pruna.ai/en/stable/) for more 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,
    "distributer": null,
    "enhancer": null,
    "factorizer": null,
    "kernel": null,
    "pruner": null,
    "quantizer": null,
    "recoverer": null,
    "batch_size": 1,
    "device": "cpu",
    "device_map": null,
    "save_fns": [],
    "load_fns": [
        "diffusers"
    ],
    "reapply_after_load": {
        "factorizer": null,
        "pruner": null,
        "quantizer": null,
        "distiller": null,
        "kernel": null,
        "cacher": null,
        "recoverer": null,
        "distributer": null,
        "compiler": null,
        "batcher": null,
        "enhancer": null
    }
}
```

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