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Check out the documentation for more information.

Paper: Calibri: Enhancing Diffusion Transformers via Parameter-Efficient Calibration

Calibri Flux with gates calibration

Guide to run:

import torch
from diffusers import DiffusionPipeline
        
device = "cuda" if torch.cuda.is_available() else "cpu"
dtype = torch.bfloat16
model_path = "v-gen-ai/flux-calibri-gates"

pipeline = DiffusionPipeline.from_pretrained(
    model_path,
    torch_dtype=dtype
).to(device)

prompts = [
    "a futuristic city at sunset",
    "a cute robot playing guitar"
]

images = pipeline(
    prompts,
    num_inference_steps=15,
    guidance_scale=3.5,
    height=512,
    width=512,
).images

Model was trained with resolution 512 x 512, but it is possible to run with other resolutions.

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