Instructions to use azikimbowe/zit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use azikimbowe/zit with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("azikimbowe/zit", 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
Ctrl+K
- DAF-ZIT-full-v1-run1_000000900
- DAF-ZIT-full-v1-run1_000001050
- DAF-ZIT-full-v1-run1_000001200_extra-details
- DAF-ZIT-full-v1-run1_000001350_extra-details
- DAF-ZIT-full-v1-run1_000001500_extra-details
- DAF-ZIT-full-v1-run1_000001650_extra-details
- DAF-ZIT-full-v1-run1_000001800_extra-details
- ZIT_FT_v2_000015000
- ZIT_FT_v2_000021500
- ZIT_FT_v2_000030000
- checkpointV2_7500
- checkpointV3_15000
- checkpointV3_20250
- checkpointV3_7500
- checkpointV4_10000
- checkpointV4_12000
- checkpointV4_6000
- checkpointV4_6500
- checkpointV4_8000
- checkpoint_18000
- 1.52 kB