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|
|
| # OpenVINO |
|
|
| 🤗 [Optimum](https://github.com/huggingface/optimum-intel) provides Stable Diffusion pipelines compatible with OpenVINO to perform inference on a variety of Intel processors (see the [full list](https://docs.openvino.ai/latest/openvino_docs_OV_UG_supported_plugins_Supported_Devices.html) of supported devices). |
|
|
| You'll need to install 🤗 Optimum Intel with the `--upgrade-strategy eager` option to ensure [`optimum-intel`](https://github.com/huggingface/optimum-intel) is using the latest version: |
|
|
| ```bash |
| pip install --upgrade-strategy eager optimum["openvino"] |
| ``` |
|
|
| This guide will show you how to use the Stable Diffusion and Stable Diffusion XL (SDXL) pipelines with OpenVINO. |
|
|
| ## Stable Diffusion |
|
|
| To load and run inference, use the [`~optimum.intel.OVStableDiffusionPipeline`]. If you want to load a PyTorch model and convert it to the OpenVINO format on-the-fly, set `export=True`: |
|
|
| ```python |
| from optimum.intel import OVStableDiffusionPipeline |
| |
| model_id = "runwayml/stable-diffusion-v1-5" |
| pipeline = OVStableDiffusionPipeline.from_pretrained(model_id, export=True) |
| prompt = "sailing ship in storm by Rembrandt" |
| image = pipeline(prompt).images[0] |
| |
| # Don't forget to save the exported model |
| pipeline.save_pretrained("openvino-sd-v1-5") |
| ``` |
|
|
| To further speed-up inference, statically reshape the model. If you change any parameters such as the outputs height or width, you’ll need to statically reshape your model again. |
|
|
| ```python |
| # Define the shapes related to the inputs and desired outputs |
| batch_size, num_images, height, width = 1, 1, 512, 512 |
| |
| # Statically reshape the model |
| pipeline.reshape(batch_size, height, width, num_images) |
| # Compile the model before inference |
| pipeline.compile() |
| |
| image = pipeline( |
| prompt, |
| height=height, |
| width=width, |
| num_images_per_prompt=num_images, |
| ).images[0] |
| ``` |
| <div class="flex justify-center"> |
| <img src="https://huggingface.co/datasets/optimum/documentation-images/resolve/main/intel/openvino/stable_diffusion_v1_5_sail_boat_rembrandt.png"> |
| </div> |
| |
| You can find more examples in the 🤗 Optimum [documentation](https://huggingface.co/docs/optimum/intel/inference#stable-diffusion), and Stable Diffusion is supported for text-to-image, image-to-image, and inpainting. |
|
|
| ## Stable Diffusion XL |
|
|
| To load and run inference with SDXL, use the [`~optimum.intel.OVStableDiffusionXLPipeline`]: |
|
|
| ```python |
| from optimum.intel import OVStableDiffusionXLPipeline |
| |
| model_id = "stabilityai/stable-diffusion-xl-base-1.0" |
| pipeline = OVStableDiffusionXLPipeline.from_pretrained(model_id) |
| prompt = "sailing ship in storm by Rembrandt" |
| image = pipeline(prompt).images[0] |
| ``` |
|
|
| To further speed-up inference, [statically reshape](#stable-diffusion) the model as shown in the Stable Diffusion section. |
|
|
| You can find more examples in the 🤗 Optimum [documentation](https://huggingface.co/docs/optimum/intel/inference#stable-diffusion-xl), and running SDXL in OpenVINO is supported for text-to-image and image-to-image. |
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|