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
- Draw Things
- DiffusionBee
| { | |
| "crop_size": { | |
| "height": 224, | |
| "width": 224 | |
| }, | |
| "do_center_crop": true, | |
| "do_convert_rgb": true, | |
| "do_normalize": true, | |
| "do_rescale": true, | |
| "do_resize": true, | |
| "image_mean": [ | |
| 0.48145466, | |
| 0.4578275, | |
| 0.40821073 | |
| ], | |
| "image_processor_type": "CLIPImageProcessor", | |
| "image_std": [ | |
| 0.26862954, | |
| 0.26130258, | |
| 0.27577711 | |
| ], | |
| "resample": 3, | |
| "rescale_factor": 0.00392156862745098, | |
| "size": { | |
| "shortest_edge": 224 | |
| } | |
| } | |