Instructions to use VHKE/modell with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use VHKE/modell 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/modell") prompt = "Modell" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
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Download README.md from VHKE/modell: direct link, hf CLI and curl.
- Browser
- Download file 777 Bytes
-
https://huggingface.co/VHKE/modell/resolve/main/README.md
- Command line
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hf download hf://VHKE/modell/README.md
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curl -L -o README.md https://huggingface.co/VHKE/modell/resolve/main/README.md
777 Bytes
metadata
tags:
- text-to-image
- flux
- lora
- diffusers
- template:sd-lora
- fluxgym
widget:
- output:
url: sample/modell_004500_00_20241219085844.png
text: Modell
base_model: black-forest-labs/FLUX.1-dev
instance_prompt: Modell
license: other
license_name: flux-1-dev-non-commercial-license
license_link: https://huggingface.co/black-forest-labs/FLUX.1-dev/blob/main/LICENSE.md
Modell
A Flux LoRA trained on a local computer with Fluxgym

- Prompt
- Modell
Trigger words
You should use Modell 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.