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("XLabs-AI/flux-RealismLora")
prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
image = pipe(prompt).images[0]
This repository provides a checkpoint with trained LoRA photorealism for FLUX.1-dev model by Black Forest Labs
ComfyUI
See our github for comfy ui workflows.
Training details
XLabs AI team is happy to publish fine-tuning Flux scripts, including:
- LoRA π₯
- ControlNet π₯
See our github for train script and train configs.
Training Dataset
Dataset has the following format for the training process:
βββ images/
β βββ 1.png
β βββ 1.json
β βββ 2.png
β βββ 2.json
β βββ ...
A .json file contains "caption" field with a text prompt.
Inference
python3 demo_lora_inference.py \
--checkpoint lora.safetensors \
--prompt " handsome girl in a suit covered with bold tattoos and holding a pistol. Animatrix illustration style, fantasy style, natural photo cinematic"
License
lora.safetensors falls under the FLUX.1 [dev] Non-Commercial License
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Model tree for XLabs-AI/flux-RealismLora
Base model
black-forest-labs/FLUX.1-dev