Instructions to use mugheesmirza/mirza-sd-task-ml1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use mugheesmirza/mirza-sd-task-ml1 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("mugheesmirza/mirza-sd-task-ml1", 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
Mirza_SD_Task_ML1 Dreambooth model trained by mugheesmirza with TheLastBen's fast-DreamBooth notebook
Test the concept via A1111 Colab fast-Colab-A1111
Sample pictures of this concept:
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