# How to use OpenVINO for inference 🤗 [Optimum](https://github.com/huggingface/optimum-intel) provides Stable Diffusion pipelines compatible with OpenVINO. You can now easily perform inference with OpenVINO Runtime on a variety of Intel processors ([see](https://docs.openvino.ai/latest/openvino_docs_OV_UG_supported_plugins_Supported_Devices.html) the full list of supported devices). ## Installation Install 🤗 Optimum Intel with the following command: ``` pip install --upgrade-strategy eager optimum["openvino"] ``` The `--upgrade-strategy eager` option is needed to ensure [`optimum-intel`](https://github.com/huggingface/optimum-intel) is upgraded to its latest version. ## Stable Diffusion ### Inference To load an OpenVINO model and run inference with OpenVINO Runtime, you need to replace `StableDiffusionPipeline` with `OVStableDiffusionPipeline`. In case you want to load a PyTorch model and convert it to the OpenVINO format on-the-fly, you can 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, the model can be statically reshaped : ```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] ``` In case you want to change any parameters such as the outputs height or width, you’ll need to statically reshape your model once again.

### Supported tasks | Task | Loading Class | |--------------------------------------|--------------------------------------| | `text-to-image` | `OVStableDiffusionPipeline` | | `image-to-image` | `OVStableDiffusionImg2ImgPipeline` | | `inpaint` | `OVStableDiffusionInpaintPipeline` | You can find more examples in the optimum [documentation](https://huggingface.co/docs/optimum/intel/inference#stable-diffusion). ## Stable Diffusion XL ### Inference ```python from optimum.intel import OVStableDiffusionXLPipeline model_id = "stabilityai/stable-diffusion-xl-base-1.0" pipeline = OVStableDiffusionXLPipeline.from_pretrained(model_id, export=True) prompt = "sailing ship in storm by Rembrandt" image = pipeline(prompt).images[0] ``` To further speed up inference, the model can be statically reshaped as showed above. You can find more examples in the optimum [documentation](https://huggingface.co/docs/optimum/intel/inference#stable-diffusion-xl). ### Supported tasks | Task | Loading Class | |--------------------------------------|--------------------------------------| | `text-to-image` | `OVStableDiffusionXLPipeline` | | `image-to-image` | `OVStableDiffusionXLImg2ImgPipeline` |