Nitro-AR

pip install diffusers==0.32.2 transformers==4.49.0 accelerate==1.7.0 wandb torchmetrics pycocotools torchmetrics[image] mosaicml-streaming==0.11.0 beautifulsoup4 tabulate timm==0.9.1 pyarrow einops omegaconf sentencepiece==0.2.0 pandas==2.2.3 alive-progress ftfy peft safetensors

from core.tools.inference_pipe import init_pipe
import torch

device = torch.device('cuda')
dtype = torch.bfloat16

# Initialize pipeline for 'gan' model (Adversarial Fine-tuned, 3 steps)
pipe = init_pipe(device, dtype, model_type='gan')

# Run inference
prompt = "a photo of a dog, with a white background"
output = pipe(prompt=prompt)
output.images[0].save("output_gan.png")

# Initialize pipeline for 'joint_gan' model (Joint Sampling + Adversarial Fine-tuned, 6 steps)
pipe_joint = init_pipe(device, dtype, model_type='joint_gan')

# Run inference
output_joint = pipe_joint(prompt=prompt)
output_joint.images[0].save("output_joint_gan.png")