infer.py

import os
import argparse
import torch
from diffusers import StableDiffusionPipeline, StableDiffusionXLPipeline, AutoPipelineForText2Image, LCMScheduler

from optimum.intel.openvino import OVLatentConsistencyModelPipeline, OVWeightQuantizationConfig
import time
import datasets

prompt = "sailing ship in storm by Rembrandt"    
#model_id = "./LCM_Dreamshaper_v7-ov-int8"
model_id = "rippertnt/canvers-dream-v1.0.0-lcm-ov-int8"
#quantization_config = OVWeightQuantizationConfig(bits=8, dataset="conceptual_captions")
pipeline = OVLatentConsistencyModelPipeline.from_pretrained(model_id, bits=8)#,quantization_config=quantization_config)
start = time.time()
print("inference")
image = pipeline(prompt, num_inference_steps=4, guidance_scale=8.0, height=512, width=512).images[0]

print(time.time() - start )
image.save("test2.png")