Create README.md
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README.md
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---
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pipeline_tag: text-to-image
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---
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# Model Card for stable-diffusion-1.5_iofp32_amdgpu
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Model was converted from https://huggingface.co/stable-diffusion-v1-5/stable-diffusion-v1-5 with additional AMD Optimizations
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## How to Get Started with the Model
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Use the code below to get started with the model.
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With Python using Diffusers OnnxStableDiffusionPipeline
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Required Modules
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```
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accelerate
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numpy==1.26.4 # Due to newer version of numpy changing dtype when multiplying
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diffusers
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torch
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transformers
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onnxruntime-directml
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```
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Python Script
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```
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import onnxruntime as ort
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from diffusers import OnnxStableDiffusionPipeline
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model_dir = "D:\\Models\\stable-diffusion-v1-5_io32"
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batch_size = 1
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num_inference_steps = 30
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image_size = 512
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guidance_scale = 7.5
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prompt = "a beautiful cabin in the mountains of Lake Tahoe"
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ort.set_default_logger_severity(3)
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sess_options = ort.SessionOptions()
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sess_options.enable_mem_pattern = False
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sess_options.add_free_dimension_override_by_name("unet_sample_batch", batch_size * 2)
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sess_options.add_free_dimension_override_by_name("unet_sample_channels", 4)
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sess_options.add_free_dimension_override_by_name("unet_sample_height", image_size // 8)
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sess_options.add_free_dimension_override_by_name("unet_sample_width", image_size // 8)
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sess_options.add_free_dimension_override_by_name("unet_time_batch", batch_size)
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sess_options.add_free_dimension_override_by_name("unet_hidden_batch", batch_size * 2)
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sess_options.add_free_dimension_override_by_name("unet_hidden_sequence", 77)
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pipeline = OnnxStableDiffusionPipeline.from_pretrained(
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model_dir, provider="DmlExecutionProvider", sess_options=sess_options
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)
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result = pipeline(
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[prompt] * batch_size,
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num_inference_steps=num_inference_steps,
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callback=None,
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height=image_size,
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width=image_size,
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guidance_scale=guidance_scale,
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generator=None
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)
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output_path = "output.png"
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result.images[0].save(output_path)
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print(f"Generated {output_path}")
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```
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### Inference Results
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