Instructions to use nphSi/Z-Image-Lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use nphSi/Z-Image-Lora with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Tongyi-MAI/Z-Image,Tongyi-MAI/Z-Image-Turbo", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("nphSi/Z-Image-Lora") prompt = "Alexandra Chando (vrtlAlexandraChando)" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
Update-Frequency based on current Runpod funds: 6+ Loras per Day
#41
pinned
by nphSi - opened
Add funds here https://ko-fi.com/nphsi to raise number of new Loras per update each day.
Remember you vote with your wallet.
Edit: Updated to 6+ Loras/Day
Thanks to my supporters!
- Preview for upcoming updates (08.May.26):
nphSi pinned discussion
It’s actually pathetic that no one else has dropped a tip yet. No wonder that content elsewhere is hidden behind a Patreon paywall, because apparently, that’s the only way people pay up. Step it up—if you're grabbing Loras, you've definitely got a coffee to spare...
nphSi changed discussion title from Update-Frequency based on current Runpod funds: 2 Loras per Day to Update-Frequency based on current Runpod funds: 4 Loras per Day
nphSi changed discussion title from Update-Frequency based on current Runpod funds: 4 Loras per Day to Update-Frequency based on current Runpod funds: 6+ Loras per Day
