Instructions to use BackTo2014/DDPM-test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use BackTo2014/DDPM-test with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("BackTo2014/DDPM-test", 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
| { | |
| "in_channels": 3, | |
| "out_channels": 3, | |
| "down_block_types": [ | |
| "DownBlock2D", | |
| "DownBlock2D", | |
| "AttnDownBlock2D", | |
| "DownBlock2D" | |
| ], | |
| "up_block_types": [ | |
| "UpBlock2D", | |
| "AttnUpBlock2D", | |
| "UpBlock2D", | |
| "UpBlock2D" | |
| ], | |
| "block_out_channels": [ | |
| 128, 256, 384, 512 | |
| ], | |
| "layers_per_block": 2, | |
| "norm_num_groups": 32, | |
| "cross_attention_dim": null, | |
| "attention_head_dim": 8, | |
| "resnet_time_scale_shift": "default", | |
| "class_embed_type": null, | |
| "num_class_embeds": null, | |
| "use_linear_projection": false, | |
| "only_cross_attention": false, | |
| "mid_block_scale_factor": 1, | |
| "out_bias": true, | |
| "flip_sin_to_cos": true, | |
| "freq_shift": 0 | |
| } |