Instructions to use jpuri/multi-view-diffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use jpuri/multi-view-diffusion with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("jpuri/multi-view-diffusion", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
File size: 403 Bytes
73f9d15 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 | {
"_class_name": "MultiViewUNetModel",
"_diffusers_version": "0.25.0",
"attention_resolutions": [
4,
2,
1
],
"camera_dim": 16,
"channel_mult": [
1,
2,
4,
4
],
"context_dim": 1024,
"image_size": 32,
"in_channels": 4,
"ip_dim": 16,
"model_channels": 320,
"num_head_channels": 64,
"num_res_blocks": 2,
"out_channels": 4,
"transformer_depth": 1
}
|