OpenVINO/stable-diffusion-1-5-quantized

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Introduction of OpenVINO/stable-diffusion-1-5-quantized

Model Details of OpenVINO/stable-diffusion-1-5-quantized

stable-diffusion-v1-5-int8-quant

Description

This is runwayml/stable-diffusion-v1-5 model converted to the OpenVINO™ IR (Intermediate Representation) format with weights compressed to INT8 by NNCF .

Quantization Parameters

Weight compression was performed using nncf.compress_weights with the following parameters:

  • mode: INT8_ASYM
  • ratio: 1.0

For more information on quantization, check the OpenVINO model optimization guide .

Running Model Inference
  1. Install packages required for using Optimum Intel integration with the OpenVINO backend:
pip install optimum[openvino]
  1. Run model inference:
from optimum.intel.openvino import OVStableDiffusionPipeline

model_id = "OpenVINO/stable-diffusion-v1-5-int8-quant"
pipeline = OVStableDiffusionPipeline.from_pretrained(model_id)
pipeline.reshape(batch_size=1, height=512, width=512, num_images_per_prompt=1)
pipeline.compile()

prompt = "plant pokemon in jungle"
output = pipeline(prompt, num_inference_steps=50, output_type="pil")
output.images[0].save("result.png")
Usage examples
Limitations

Check the original model card for limitations .

Legal information

The original model is distributed under creativeml-openrail-m license. More details can be found in runwayml/stable-diffusion-v1-5 .

Disclaimer

Intel is committed to respecting human rights and avoiding causing or contributing to adverse impacts on human rights. See Intel’s Global Human Rights Principles . Intel’s products and software are intended only to be used in applications that do not cause or contribute to adverse impacts on human rights.

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OpenVINO/stable-diffusion-1-5-quantized install

OpenVINO/stable-diffusion-1-5-quantized is an open source model from GitHub that offers a free installation service, and any user can find OpenVINO/stable-diffusion-1-5-quantized on GitHub to install. At the same time, huggingface.co provides the effect of OpenVINO/stable-diffusion-1-5-quantized install, users can directly use OpenVINO/stable-diffusion-1-5-quantized installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

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