Instructions to use VHKE/fodg with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use VHKE/fodg 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("VHKE/fodg") prompt = "fodg packaging bag of Flexadin sitting on a tablt --d 45" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
fodg
A Flux LoRA trained on a local computer with Fluxgym

- Prompt
- fodg packaging bag of Flexadin sitting on a tablt --d 45

- Prompt
- fodg packaging bag of Flexadin sitting next to a mountain dog --d 45
Trigger words
You should use fodg 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.
- Downloads last month
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Model tree for VHKE/fodg
Base model
black-forest-labs/FLUX.1-dev