Text-to-Image
Diffusers
Safetensors
StableDiffusionPipeline
Art
DucHaiten
stable-diffusion
stable-diffusion-diffusers
Instructions to use Yntec/DucHaitenAIart-beta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Yntec/DucHaitenAIart-beta with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Yntec/DucHaitenAIart-beta", 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 Settings
- Draw Things
- DiffusionBee
Fixing model settings
#4
by Yntec - opened
If your model converted to diffusers doesn't work on the Inference API, or it produces bad quality outputs, plugging it on the Model Converter and making a "Fp32" "No Ema" version will be enough to fix it. However, for a model that is +7.7GB in size, like this one, you can't do that because you will run out of memory before it finishes saving.
What I did instead was using the model OldFish 1.1 that is only 1.8GB, to create an Alpha 1.0 merge in supermerger, and used the settings below to create a no ema version of this model that the inference API can use to produce images of good quality:
