Instructions to use gsalami/gulorasynth with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use gsalami/gulorasynth 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("gsalami/gulorasynth") prompt = "gusynth01" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
gulorasynth
Model description
a small lara with 10 synthetic images
Trigger words
You should use gusynth01 to trigger the image generation.
Download model
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.
Training at fal.ai
Training was done using fal.ai/models/fal-ai/flux-lora-fast-training.
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Model tree for gsalami/gulorasynth
Base model
black-forest-labs/FLUX.1-dev