Instructions to use SedatAl/manga-LoRa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use SedatAl/manga-LoRa with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("SedatAl/manga-LoRa") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
LoRA text2image fine-tuning - SedatAl/manga-LoRa
These are LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0. The weights were fine-tuned on the Chan-Y/Manga-Drawings dataset.

Special VAE used for training: madebyollin/sdxl-vae-fp16-fix.
How to use
resolution=1024
train_batch_size=1
gradient_accumulation_steps=4
max_train_steps=528
learning_rate=1e-4
lr_scheduler="cosine"
lr_warmup_steps=100
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Model tree for SedatAl/manga-LoRa
Base model
stabilityai/stable-diffusion-xl-base-1.0