Ddpm Bedroom Finetuned Texture Dtd 1ep Bs4
Bedroom model fine-tuned using dtd textures. Investigating pink problem
Modellquelle
- Art
- Other
- Dateigröße
- 434 MB
- Version
- vRevision a441f0b
- Aktualisiert
- 27. Sept. 2026
- Downloads
- 5
- Quelle
- Hugging Face
Quellenbeschreibung
Description
Bedroom model fine-tuned using dtd textures. Investigating pink problem
Usage
from diffusers import DDPMPipeline
# Load the pretrained pipeline
pipeline_name = "ttextture/ddpm-bedroom-finetuned-texture-dtd"
image_pipe = DDPMPipeline.from_pretrained(pipeline_name).to(device)
# Sample some images with a DDIM Scheduler over 40 steps
scheduler = DDIMScheduler.from_pretrained(pipeline_name)
scheduler.set_timesteps(num_inference_steps=40)
image = pipeline().images[0]
image
Quellen
1 Quelle
Quellen
1 QuelleVerifiziert 7. Sept.
Modellartefakte
1 Artefakt
Modellartefakte
1 Artefaktdiffusion_pytorch_model.safetensors
safetensors · 434 MB · SHA-256 9ecf3b501fec…c68f · Hugging Face
HerunterladenQuellenauszüge
2 Auszüge
Quellenauszüge
2 Auszüge--- license: mit tags: - pytorch - diffusers - unconditional-image-generation - diffusion-models-class --- # Description Bedroom model fine-tuned using dtd textures. Investigating pink problem ## Usage ```python from diffusers import DDPMPipeline # Load the pretrained pipeline pipeline_name = "ttextture/ddpm-bedroom-finetuned-texture-dtd" image_pipe = DDPMPipeline.from_pretrained(pipeline_name).to(device) # Sample some images with a DDIM Scheduler over 40 steps scheduler = DDIMScheduler.from_pretrained(pipeline_name) scheduler.set_timesteps(num_inference_steps=40) image = pipeline().images[0] image ```
Source context: 5 downloads · 0 likes · Pipeline unconditional-image-generation · Library diffusers · Repo ttextture/ddpm-bedroom-finetuned-texture-dtd-1ep-bs4
