---
license: creativeml-openrail-m
tags:
- safetensors
- pruna-ai
widget:
- text: A high tech solarpunk utopia in the Amazon rainforest
  example_title: Amazon rainforest
- text: A pikachu fine dining with a view to the Eiffel Tower
  example_title: Pikachu in Paris
- text: A mecha robot in a favela in expressionist style
  example_title: Expressionist robot
- text: an insect robot preparing a delicious meal
  example_title: Insect robot
- text: A small cabin on top of a snowy mountain in the style of Disney, artstation
  example_title: Snowy disney cabin
extra_gated_prompt: "This model is open access and available to all, with a CreativeML\
  \ OpenRAIL-M license further specifying rights and usage.\nThe CreativeML OpenRAIL\
  \ License specifies: \n\n1. You can't use the model to deliberately produce nor\
  \ share illegal or harmful outputs or content \n2. The authors claim no rights on\
  \ the outputs you generate, you are free to use them and are accountable for their\
  \ use which must not go against the provisions set in the license\n3. You may re-distribute\
  \ the weights and use the model commercially and/or as a service. If you do, please\
  \ be aware you have to include the same use restrictions as the ones in the license\
  \ and share a copy of the CreativeML OpenRAIL-M to all your users (please read the\
  \ license entirely and carefully)\nPlease read the full license carefully here:\
  \ https://huggingface.co/spaces/CompVis/stable-diffusion-license\n    "
extra_gated_heading: Please read the LICENSE to access this model
---

# Model Card for TensorVizion/StableDiffusion-1.4-Pruned

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 library_name library to load the model](https://huggingface.co/TensorVizion/StableDiffusion-1.4-Pruned?library=library_name) 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_pretrained(
    "TensorVizion/StableDiffusion-1.4-Pruned"
)
# we can then run inference using the methods supported by the base model
```

 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
{
    "awq": false,
    "c_generate": false,
    "c_translate": false,
    "c_whisper": false,
    "deepcache": true,
    "diffusers_int8": false,
    "fastercache": false,
    "flash_attn3": false,
    "fora": false,
    "gptq": false,
    "half": false,
    "hqq": false,
    "hqq_diffusers": false,
    "hyper": false,
    "ifw": false,
    "img2img_denoise": false,
    "kvpress": false,
    "llama_cpp": false,
    "llm_int8": false,
    "moe_kernel_tuner": false,
    "pab": false,
    "padding_pruning": false,
    "qkv_diffusers": false,
    "quanto": false,
    "realesrgan_upscale": false,
    "reduce_noe": false,
    "ring_attn": false,
    "sage_attn": false,
    "stable_fast": 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,
    "x_fast": false,
    "zipar": false,
    "deepcache_interval": 2,
    "batch_size": 1,
    "device": "cuda",
    "device_map": null,
    "save_fns": [],
    "save_artifacts_fns": [],
    "load_fns": [
        "diffusers"
    ],
    "load_artifacts_fns": [],
    "reapply_after_load": {
        "deepcache": true
    }
}
```

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