File size: 4,073 Bytes
43c8e42
 
 
501ae8b
1755522
3729da6
43c8e42
 
b5e119e
43c8e42
 
 
 
 
 
 
 
 
 
 
b5e119e
43c8e42
 
 
 
 
 
 
b5e119e
43c8e42
 
 
 
 
 
 
 
 
 
 
 
 
 
51f1eba
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
61567b9
51f1eba
6628b8b
51f1eba
 
 
 
 
 
4971c9d
51f1eba
cf34dcb
51f1eba
09e4674
51f1eba
 
 
 
 
 
 
 
 
 
 
 
6f75ba8
51f1eba
 
 
 
 
 
 
 
 
43c8e42
 
 
 
73b77e8
43c8e42
 
 
73b77e8
51f1eba
43c8e42
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
---
library_name: diffusers
tags:
- safetensors
- pruna_pro-ai
- pruna-ai
---

# Model Card for pruna-test/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/pruna-test/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(
    "pruna-test/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
{
    "adaptive": false,
    "auto": false,
    "awq": false,
    "bottleneck": false,
    "c_generate": false,
    "c_translate": false,
    "c_whisper": false,
    "deepcache": false,
    "diffusers_higgs": false,
    "diffusers_int8": false,
    "fastercache": false,
    "flash_attn3": false,
    "flux_caching": false,
    "fora": false,
    "fp4": false,
    "fp8": false,
    "gptq": false,
    "half": false,
    "higgs": false,
    "hqq": false,
    "hqq_diffusers": false,
    "hyper": false,
    "ifw": false,
    "img2img_denoise": false,
    "ipex_llm": false,
    "kvpress": false,
    "llm_int8": false,
    "moe_kernel_tuner": false,
    "pab": false,
    "padding_pruning": false,
    "periodic": false,
    "prores": false,
    "qkv_diffusers": false,
    "quanto": false,
    "radial_attn": false,
    "realesrgan_upscale": false,
    "reduce_noe": false,
    "ring_attn": false,
    "sage_attn": false,
    "stable_fast": false,
    "taylor": false,
    "taylor_auto": false,
    "text_to_image_distillation_inplace_perp": false,
    "text_to_image_distillation_lora": false,
    "text_to_image_distillation_perp": false,
    "text_to_image_inplace_perp": false,
    "text_to_image_lora": false,
    "text_to_image_perp": false,
    "text_to_text_inplace_perp": false,
    "text_to_text_lora": false,
    "text_to_text_perp": false,
    "token_merging": false,
    "torch_compile": false,
    "torch_dynamic": false,
    "torch_structured": false,
    "torch_unstructured": false,
    "torchao": false,
    "torchao_autoquant": false,
    "whisper_s2t": false,
    "x_fast": false,
    "zipar": false,
    "batch_size": 1,
    "device": "cpu",
    "device_map": null,
    "save_fns": [],
    "save_artifacts_fns": [],
    "load_fns": [
        "diffusers"
    ],
    "load_artifacts_fns": [],
    "reapply_after_load": {}
}
```

## 🌍 Join the Pruna AI community!

[![Twitter](https://img.shields.io/twitter/follow/PrunaAI?style=social)](https://twitter.com/PrunaAI)
[![GitHub](https://img.shields.io/github/followers/PrunaAI?label=Follow%20%40PrunaAI&style=social)](https://github.com/PrunaAI)
[![LinkedIn](https://img.shields.io/badge/LinkedIn-Connect-blue)](https://www.linkedin.com/company/93832878/admin/feed/posts/?feedType=following)
[![Discord](https://img.shields.io/badge/Discord-Join%20Us-blue?style=social&logo=discord)](https://discord.gg/JFQmtFKCjd)
[![Reddit](https://img.shields.io/reddit/subreddit-subscribers/PrunaAI?style=social)](https://www.reddit.com/r/PrunaAI/)