Instructions to use BiliSakura/DDIB-ckpt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use BiliSakura/DDIB-ckpt with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("BiliSakura/DDIB-ckpt", 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: 280 Bytes
cbe01d4 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | {
"in_channels": 3,
"model_channels": 256,
"out_channels": 6,
"num_res_blocks": 3,
"attention_resolutions": [
2,
4,
8
],
"channel_mult": [
1,
2,
2,
4
],
"time_embed_dim": 512,
"use_scale_shift_norm": true,
"conv_resample": false
} |