Create README.md

README.md

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+---
+pipeline_tag: text-to-image
+---
+# stable-diffusion-1.5 optimized for AMD GPU
+
+
+## Original Model
+https://huggingface.co/stable-diffusion-v1-5/stable-diffusion-v1-5
+
+## _io32/16
+_io32: model input is fp32, model will convert the input to fp16, perform ops in fp16 and write the final result in fp32
+
+_io16: model input is fp16, perform ops in fp16 and write the final result in fp16
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+With Python using Diffusers OnnxStableDiffusionPipeline
+
+Required Modules
+```
+accelerate
+numpy==1.26.4 # Due to newer version of numpy changing dtype when multiplying
+diffusers
+torch
+transformers
+onnxruntime-directml
+```
+
+Python Script
+```
+import onnxruntime as ort
+from diffusers import OnnxStableDiffusionPipeline
+
+model_dir = "D:\\Models\\stable-diffusion-v1-5_io32"
+
+batch_size = 1
+num_inference_steps = 30
+image_size = 512
+guidance_scale = 7.5
+prompt = "a beautiful cabin in the mountains of Lake Tahoe"
+
+ort.set_default_logger_severity(3)
+
+sess_options = ort.SessionOptions()
+sess_options.enable_mem_pattern = False
+
+sess_options.add_free_dimension_override_by_name("unet_sample_batch", batch_size * 2)
+sess_options.add_free_dimension_override_by_name("unet_sample_channels", 4)
+sess_options.add_free_dimension_override_by_name("unet_sample_height", image_size // 8)
+sess_options.add_free_dimension_override_by_name("unet_sample_width", image_size // 8)
+sess_options.add_free_dimension_override_by_name("unet_time_batch", batch_size)
+sess_options.add_free_dimension_override_by_name("unet_hidden_batch", batch_size * 2)
+sess_options.add_free_dimension_override_by_name("unet_hidden_sequence", 77)
+
+pipeline = OnnxStableDiffusionPipeline.from_pretrained(
+    model_dir, provider="DmlExecutionProvider", sess_options=sess_options
+)
+
+result = pipeline(
+        [prompt] * batch_size,
+        num_inference_steps=num_inference_steps,
+        callback=None,
+        height=image_size,
+        width=image_size,
+        guidance_scale=guidance_scale,
+        generator=None
+    )
+
+output_path = "output.png"
+result.images[0].save(output_path)
+
+print(f"Generated {output_path}")
+```
+
+### Inference Results
+
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/65f275d7b06ca1ff48a356fb/g93w4ATPtUZndc0Dt9Smp.png)
+
+