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Test Save Tiny Stable Diffusion Pipe Smashed Pro

This model was created using the pruna library. Pruna is a model optimization framework built for developers, enabling you to deliver more efficient models with minimal implementation overhead.

KindOtherVersionRevision b2fa365Unratedgrade

Model source

Kind
Other
File size
58.4–241 KB
Version
vRevision b2fa365
Updated
Nov 5, 2026
Downloads
469
Source
Hugging Face

Source description

Model Card for pruna-test/test-save-tiny-stable-diffusion-pipe-smashed-pro

This model was created using the 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:

pip install pruna_pro

You can use the library_name library to load the model 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:

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

Alternatively, you can visit the Pruna documentation 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.

{
    "adaptive": false,
    "auto": false,
    "awq": false,
    "bottleneck": false,
    "c_generate": false,
    "c_translate": false,
    "c_whisper": false,
    "custom_schedule": 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,
    "kvpress": false,
    "llama_cpp": 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,
    "static_fp8_diffusers": 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,
    "time_aware_fp8_diffusers": false,
    "token_merging": false,
    "torch_compile": false,
    "torch_dynamic": false,
    "torch_structured": false,
    "torch_unstructured": false,
    "torchao": false,
    "torchao_autoquant": 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": {}
}

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Sources

1 source
Hugging FacePrimaryVersion b2fa3651df6a3422e523eda2bfe51d5e18b855c5
huggingface.co/pruna-test/test-save-tiny-stable-diffusion-pipe-smashed-pro/tree/b2fa3651df6a3422e523eda2bfe51d5e18b855c5

Verified Nov 5

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Model artifacts

4 artifacts

safety_checker/model.safetensors

safetensors · FP32 (tensor header) · 187 KB · SHA-256 cd553c930718…cd8f · Hugging Face

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text_encoder/model.safetensors

safetensors · FP32 (tensor header) · 241 KB · SHA-256 5edffee1c2ae…0b62 · Hugging Face

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unet/diffusion_pytorch_model.safetensors

safetensors · FP32 (tensor header) · 93.8 KB · SHA-256 8f2a2ce8d558…5d46 · Hugging Face

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vae/diffusion_pytorch_model.safetensors

safetensors · FP32 (tensor header) · 58.4 KB · SHA-256 b023ca2edc02…50ef · Hugging Face

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Source excerpts

3 excerpts

--- license: apache-2.0 tags: - pruna-ai - safetensors - pruna_pro-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 library_name library to load the model](https://huggingface.co/pruna-test/test-save-tiny-stable-diffusion-pipe-smashed-pro?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_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 ``` 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, "custom_schedule": 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, "kvpress": false, "llama_cpp": 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, "static_fp8_diffusers": false, "taylor": false, "taylor_auto": false, "text_to_image_distillation_inplace_perp": false, "text_to_image_distillation_lora": false, "text_to...

--- library_name: diffusers tags: - pruna_pro-ai - safetensors - 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, "kvpress": false, "llama_cpp": 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, "ta...

Source context: 469 downloads · 1 likes · Pipeline text-to-image · Library diffusers · Repo pruna-test/test-save-tiny-stable-diffusion-pipe-smashed-pro