Instructions to use tolgacangoz/matryoshka-diffusion-models with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use tolgacangoz/matryoshka-diffusion-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("tolgacangoz/matryoshka-diffusion-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
- Local Apps
- Draw Things
- DiffusionBee
| { | |
| "_class_name": ["matryoshka", "MatryoshkaPipeline"], | |
| "_diffusers_version": "0.31.0.dev0", | |
| "feature_extractor": [ | |
| null, | |
| null | |
| ], | |
| "image_encoder": [ | |
| null, | |
| null | |
| ], | |
| "scheduler": [ | |
| "matryoshka", | |
| "MatryoshkaDDIMScheduler" | |
| ], | |
| "text_encoder": [ | |
| "transformers", | |
| "T5EncoderModel" | |
| ], | |
| "tokenizer": [ | |
| "transformers", | |
| "T5Tokenizer" | |
| ], | |
| "unet/nesting_level_0": [ | |
| "matryoshka", | |
| "MatryoshkaUNet2DConditionModel" | |
| ], | |
| "nesting_level": 0 | |
| } | |