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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.

TipoOtherVersiónRevision b2fa365Unratedcalidad

Fuente del modelo

Tipo
Other
Tamaño del archivo
58,4–241 KB
Versión
vRevision b2fa365
Actualizado
5 nov 2026
Descargas
469
Fuente
Hugging Face

Descripción de la fuente

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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Fuentes

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

Verificado 5 nov

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Artefactos del modelo

4 artefactos

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

Download file

Extractos de fuentes

3 extractos

--- 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