Text-to-Image
Diffusers
Safetensors
StableDiffusionPipeline
diffusers-training
stable-diffusion-2
stable-diffusion-2-diffusers
science
materiomics
bio-inspired
materials science
text-to-3D
text-to-STL
text-t-mesh
additive manufacturing
3D
3D printing
Instructions to use lamm-mit/SD2x-leaf-inspired with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use lamm-mit/SD2x-leaf-inspired with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("lamm-mit/SD2x-leaf-inspired", dtype=torch.bfloat16, device_map="cuda") prompt = "<leaf microstructure>" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Update README.md
Browse files
README.md
CHANGED
|
@@ -234,6 +234,9 @@ In this example, we generated a 3D model and created a physical sample using add
|
|
| 234 |
|
| 235 |

|
| 236 |
|
|
|
|
|
|
|
|
|
|
| 237 |
3D printing: Slicing using Cura and resulting physical sample with gyroid infill:
|
| 238 |
|
| 239 |

|
|
|
|
| 234 |
|
| 235 |

|
| 236 |
|
| 237 |
+
|
| 238 |
+

|
| 239 |
+
|
| 240 |
3D printing: Slicing using Cura and resulting physical sample with gyroid infill:
|
| 241 |
|
| 242 |

|