Instructions to use cocktailpeanut/kaiji-dev2pro with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use cocktailpeanut/kaiji-dev2pro 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("cocktailpeanut/kaiji-dev2pro") prompt = "kaiji style" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
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Download README.md from cocktailpeanut/kaiji-dev2pro: direct link, hf CLI and curl.
- Browser
- Download file 806 Bytes
-
https://huggingface.co/cocktailpeanut/kaiji-dev2pro/resolve/main/README.md
- Command line
-
hf download hf://cocktailpeanut/kaiji-dev2pro/README.md
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curl -L -o README.md https://huggingface.co/cocktailpeanut/kaiji-dev2pro/resolve/main/README.md
806 Bytes
metadata
tags:
- text-to-image
- flux
- lora
- diffusers
- template:sd-lora
- fluxgym
widget:
- output:
url: sample/kaiji-dev2pro_001120_00_20240925120126.png
text: kaiji style
base_model: black-forest-labs/FLUX.1-dev
instance_prompt: kaiji style
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
kaiji-dev2pro
A Flux LoRA trained on a local computer with Fluxgym

- Prompt
- kaiji style
Trigger words
You should use kaiji style 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.