Instructions to use Azam/thesis_models with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Azam/thesis_models with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Azam/thesis_models", 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
Ctrl+K
- figurine_dreambooth
- figurine_dreambooth_lora
- figurine_dreambooth_textual_inversion
- figurine_textual_inversion
- house_dreambooth
- house_dreambooth_and_textual_inversion
- house_dreambooth_lora
- house_lora
- house_textual_inversion
- mug_Dreambooth_textual_inversion
- mug_dreambooth
- mug_dreambooth_lora
- mug_lora
- mug_textual_inversion
- 1.52 kB