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
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README.md
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In this example, we generated a 3D model and created a physical sample using additive manufacturing.
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In this example, we generated a 3D model and created a physical sample using additive manufacturing.
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```
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repo_id_load= 'lamm-mit/SD2x-leaf-inspired'
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input_image=text_to_image_SD2x (base_model=repo_id_load,
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n_steps=75, guidance_scale=15,
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prompt = "a conch shell on black background that resembles a <leaf microstructure>, high quality",
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negative_prompt="" )
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display (input_image)
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processed_image, mv_images, mv_show_images= generate_multiviews (input_image, seed=None)
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display (mv_show_images)
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output_video, output_model_obj = make_multi_views_into_3D (mv_images, target_dir='output')
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Video(output_video, embed=True)
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```
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