Instructions to use lambda/sd-pokemon-diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use lambda/sd-pokemon-diffusers with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("lambda/sd-pokemon-diffusers", 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
- Local Apps
- Draw Things
- DiffusionBee
Update scheduler/scheduler_config.json
#1
by patrickvonplaten - opened
Hey!
We have introduced a steps_offset variable to scheduler configs to have a cleaner API and now want to incentivize SD schedulers to add this to the config as otherwise it'll eventually lead to silent errors.
See: https://github.com/huggingface/diffusers/blob/7258dc4943e73b8799003771e86a44424afb996d/src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion.py#L60
Best,
Diffusers Team!
Just bumping this one.
@justinpinkney could you merge it? Because else there always is a warning message about it when using the model.
Oh thanks, somehow I forgot about this!
justinpinkney changed pull request status to merged