Text-to-Image
Diffusers
diffusers-training
lora
FLUX.1-dev
science
materiomics
bio-inspired
materials science
generative AI for science
Instructions to use lamm-mit/leaf-L-FLUX.1-dev with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use lamm-mit/leaf-L-FLUX.1-dev with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("lamm-mit/leaf-L-FLUX.1-dev") prompt = "<leaf microstructure>" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Rendering notebook...
- Xet hash:
- 67c4437731b3804d7bb36e0d59c870521f3f2cd36b071258187146497cb78d2a
- Size of remote file:
- 23.6 MB
- SHA256:
- e0d2ada389ea10333d3d5f431e3f02f9b5b04a8d1eb4065c296c14abd25997a1
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