Instructions to use thangvip/compliment-forest-moonlit-gouache-flux-lora-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use thangvip/compliment-forest-moonlit-gouache-flux-lora-v2 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-schnell", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("thangvip/compliment-forest-moonlit-gouache-flux-lora-v2") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Compliment Forest moonlit_gouache FLUX LoRA
A style LoRA for black-forest-labs/FLUX.1-schnell, trained on the
moonlit_gouache configuration of
thangvip/compliment-forest-multistyle-v2. The v2 dataset balances animals,
people, symbolic objects, and environments rather than teaching an
animal-only subject prior.
Trigger
Include cmprst_moonlit near the beginning of the prompt.
Training
- Modal GPU: A100 80GB
- Resolution: 512x512
- Steps: 300
- LoRA rank/alpha: 16/16
- Learning rate: 1e-4, constant
- Guidance scale: 0
Run details are included in training-summary.json. The adapter repository is
thangvip/compliment-forest-moonlit-gouache-flux-lora-v2.
Provenance and license
Training images were generated specifically for this project with
black-forest-labs/FLUX.1-schnell through Hugging Face Inference Providers.
No named artist or known character was requested. Use remains subject to the
base model's license and terms.
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Model tree for thangvip/compliment-forest-moonlit-gouache-flux-lora-v2
Base model
black-forest-labs/FLUX.1-schnell