---
base_model: spamsoms/LCM-kotosmix_diffusers
tags:
- openvino
- openvino-export
---

This model was converted to OpenVINO from [`spamsoms/LCM-kotosmix_diffusers`](https://huggingface.co/spamsoms/LCM-kotosmix_diffusers) using [optimum-intel](https://github.com/huggingface/optimum-intel)
via the [export](https://huggingface.co/spaces/echarlaix/openvino-export) space.

First make sure you have optimum-intel installed:

```bash
pip install optimum[openvino]
```

To load your model you can do as follows:

```python
import huggingface_hub as hf_hub
from optimum.intel import OVStableDiffusionPipeline
from diffusers import  LCMScheduler
import torch


model_id = "hsuwill000/LCM-kotosmix_diffusers-openvino"

HIGH = 1024
WIDTH = 1024

batch_size = -1  # Or set it to a specific positive integer if needed

prompt="agirl, anime," 

negative_prompt="(deformed, distorted, disfigured:1.3), poorly drawn, bad anatomy, wrong anatomy,\
    extra limb, missing limb, floating limbs, (mutated hands and fingers:1.4), disconnected limbs, \
    mutation, mutated, ugly, disgusting, blurry, amputation"

pipe = OVStableDiffusionPipeline.from_pretrained(
    model_id,
    compile=False,
    ov_config={"CACHE_DIR": ""},
    torch_dtype=torch.bfloat16,  # More standard dtype for speed
    safety_checker=None,
    use_safetensors=False,
)
pipe.scheduler = LCMScheduler.from_config(pipe.scheduler.config)

print(pipe.scheduler.compatibles)
pipe.reshape(batch_size=batch_size, height=HIGH, width=WIDTH, num_images_per_prompt=1)
pipe.compile()

image = pipe(
    prompt=prompt,
    negative_prompt=negative_prompt,
    width=WIDTH,
    height=HIGH,
    guidance_scale=2,
    num_inference_steps=4,
    num_images_per_prompt=1,
).images[0]


image.save("test.png")
```