Instructions to use ostris/ideogram_4_turbotime_lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ostris/ideogram_4_turbotime_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("ideogram-ai/ideogram-4-fp8", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("ostris/ideogram_4_turbotime_lora") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
THAN A LOT! now it takes 27 sec!
#2
by napalm - opened
THAN A LOT! now it takes 27 sec!
Sadly though the results side-by-side...
Just a completely different model. 8/10 turned to 3/10
looks like nvidia's anyflow was used to train it, which does the same thing and supports n-step distillation
I wouldn't say it's become a 3/10, at least not in my tests, but the composition has indeed changed, which is expected. Sometimes the composition with the Lora is even better; for a V1, it's not bad at all, but it still needs a bit of refinement to truly show its full potential.
It's promising nonetheless, and I thank you for the work. :)
