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

- Xet hash:
- e1b3e7ecfb2a1f07e054af6a170490c0a414d52058f3a9419da30b4e01ae13ce
- Size of remote file:
- 7.25 MB
- SHA256:
- 4afb13d0b829144db3de70eeec37cb84e50012c3d055d997a8c4dac1a10f8a7c
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