import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("onkarsus13/CVVAE_Modified", dtype=torch.bfloat16, device_map="cuda")
prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
image = pipe(prompt).images[0]
from diffusers import CVVAEModel, AutoencoderKL, UNet3DConditionModelAdapter, ControlNetModel3D, ControlNetModel
import torch
import time
device = torch.device("cuda:0")
vae = CVVAEModel.from_pretrained(
"/data2/onkar/cvvae/CV-VAE",
subfolder='vae3d',
torch_dtype=torch.float16
)
vae.to(device)
print(vae)
vae.requires_grad_(False)
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