Instructions to use liming518/RodVer2Flux with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use liming518/RodVer2Flux 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("liming518/RodVer2Flux") prompt = "Image I created with this lora at 0.8, to get more face variety" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
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Download README.md from liming518/RodVer2Flux: direct link, hf CLI and curl.
- Browser
- Download file 311 Bytes
-
https://huggingface.co/liming518/RodVer2Flux/resolve/main/README.md
- Command line
-
hf download hf://liming518/RodVer2Flux/README.md
-
curl -L -o README.md https://huggingface.co/liming518/RodVer2Flux/resolve/main/README.md
311 Bytes
metadata
tags:
- text-to-image
- lora
- diffusers
- template:diffusion-lora
widget:
- text: Image I created with this lora at 0.8, to get more face variety
output:
url: images/img0.png
base_model: black-forest-labs/FLUX.1-dev
instance_prompt: null
Civitai lora for Flux1dev (deleted)

- Prompt
- Image I created with this lora at 0.8, to get more face variety