| import sys | |
| from pathlib import Path | |
| import torch | |
| from diffusers import DiffusionPipeline | |
| model_path = Path(__file__).resolve().parent | |
| sys.path.insert(0, str(model_path)) | |
| pipe = DiffusionPipeline.from_pretrained( | |
| str(model_path), | |
| custom_pipeline=str(model_path), | |
| torch_dtype=torch.bfloat16, | |
| ) | |
| pipe.to("cuda") | |
| result = pipe( | |
| prompt="A close-up portrait in a cinematic photography style, capturing a girl-next-door look on a sunny daytime urban street. She wears a khaki sweater, with long, flowing hair gently draped over her shoulders. Her head is turned slightly, revealing soft facial features illuminated by realistic, delicate sunlight coming from the left. The sunlight subtly highlights individual strands of her hair. The image has a Canon film-like color tone, evoking a warm nostalgic atmosphere.", | |
| height=1024, | |
| width=1024, | |
| num_inference_steps=50, | |
| guidance_scale=7.5, | |
| show_progress_bar=True, | |
| ) | |
| result.images[0].save("bitdance_14b_16x.png") | |
| print("Saved bitdance_14b_16x.png") | |