Instructions to use zamiipx/feetlora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use zamiipx/feetlora 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("zamiipx/feetlora") prompt = "f33tl0ra In this image we can see a blonde woman wearing black color dress is sitting on a white color cloth. In the background of the image there is a door. sole of the foot" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
feetlora
A Flux LoRA trained on a local computer with Fluxgym

- Prompt
- f33tl0ra In this image we can see a blonde woman wearing black color dress is sitting on a white color cloth. In the background of the image there is a door. sole of the foot
Trigger words
You should use f33tl0ra to trigger the image generation.
Download model and use it with ComfyUI, AUTOMATIC1111, SD.Next, Invoke AI, Forge, etc.
Weights for this model are available in Safetensors format.
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Model tree for zamiipx/feetlora
Base model
black-forest-labs/FLUX.1-dev