Instructions to use gvecchio/MatFuse with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use gvecchio/MatFuse with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("gvecchio/MatFuse", 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": "MatFuseVQModel", | |
| "_diffusers_version": "0.35.2", | |
| "attn_resolutions": [], | |
| "ch": 128, | |
| "ch_mult": [ | |
| 1, | |
| 1, | |
| 2, | |
| 4 | |
| ], | |
| "dropout": 0.0, | |
| "embed_dim": 3, | |
| "in_channels": 3, | |
| "n_embed": 4096, | |
| "num_res_blocks": 2, | |
| "out_channels": 12, | |
| "resolution": 256, | |
| "scaling_factor": 1.0, | |
| "z_channels": 256 | |
| } | |