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Vargol/
PixArt-Sigma_2k_16bit

Name: PixArt-Sigma_2k_16bit
Availability: InStock

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This Repo contains a diffusers format version of the PixArt-Sigma Repos PixArt-alpha/pixart_sigma_sdxlvae_T5_diffusers PixArt-alpha/PixArt-Sigma-XL-2-2K-MS with the models loaded and saved in fp16 and bf16 formats, roughly halfing their sizes. It can be used where download bandwith, memory or diskspace are relatively low, a T4 Colab instance for example.

NOTE: This Model has been converted but not successfully tested, during the memory effecient attention it generates 16Gb buffer, this appears break an MPS limitation, but it may also mean if requires more than 16Gb even with the 16 bit model

The diffusers script below assumes those with more memory on none MPS GPU's have more luck running it!

a Diffusers script looks like this, currently (25th April 2024) you need will to install diffusers from source.

import random
import sys
import torch
from diffusers from PixArtSigmaPipeline

device = 'mps'
weight_dtype = torch.bfloat16

pipe = PixArtSigmaPipeline.from_pretrained(
    "Vargol/PixArt-Sigma_2k_16bit",
    torch_dtype=weight_dtype,
    variant="fp16",
    use_safetensors=True,
)

# Enable memory optimizations.
# pipe.enable_model_cpu_offload()
pipe.to(device)

prompt = "Cinematic science fiction film still.A cybernetic demon awaits her friend in a bar selling flaming oil drinks.  The barman is a huge tree being, towering over the demon"

for i in range(4):

    seed = random.randint(0, sys.maxsize)
    generator =  torch.Generator("mps").manual_seed(seed);

    image = pipe(prompt, generator=generator, num_iferencenum_inference_steps=40).images[0]
    image.save(f"pas_{seed}.png")a
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