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Update README.md

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@@ -17,8 +17,51 @@ pip install optimum[openvino]
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  To load your model you can do as follows:
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  ```python
 
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  from optimum.intel import OVStableDiffusionPipeline
 
 
 
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  model_id = "hsuwill000/LCM-kotosmix_diffusers-openvino"
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- model = OVStableDiffusionPipeline.from_pretrained(model_id)
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ```
 
 
 
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  To load your model you can do as follows:
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  ```python
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+ import huggingface_hub as hf_hub
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  from optimum.intel import OVStableDiffusionPipeline
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+ from diffusers import LCMScheduler
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+ import torch
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+
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  model_id = "hsuwill000/LCM-kotosmix_diffusers-openvino"
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+
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+ HIGH = 1024
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+ WIDTH = 1024
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+
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+ batch_size = -1 # Or set it to a specific positive integer if needed
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+
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+ prompt="agirl, anime,"
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+
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+ negative_prompt="(deformed, distorted, disfigured:1.3), poorly drawn, bad anatomy, wrong anatomy,\
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+ extra limb, missing limb, floating limbs, (mutated hands and fingers:1.4), disconnected limbs, \
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+ mutation, mutated, ugly, disgusting, blurry, amputation"
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+
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+ pipe = OVStableDiffusionPipeline.from_pretrained(
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+ model_id,
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+ compile=False,
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+ ov_config={"CACHE_DIR": ""},
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+ torch_dtype=torch.bfloat16, # More standard dtype for speed
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+ safety_checker=None,
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+ use_safetensors=False,
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+ )
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+ pipe.scheduler = LCMScheduler.from_config(pipe.scheduler.config)
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+
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+ print(pipe.scheduler.compatibles)
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+ pipe.reshape(batch_size=batch_size, height=HIGH, width=WIDTH, num_images_per_prompt=1)
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+ pipe.compile()
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+
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+ image = pipe(
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+ prompt=prompt,
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+ negative_prompt=negative_prompt,
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+ width=WIDTH,
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+ height=HIGH,
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+ guidance_scale=2,
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+ num_inference_steps=4,
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+ num_images_per_prompt=1,
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+ ).images[0]
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+
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+
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+ image.save("test.png")
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  ```
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+
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+