Instructions to use sayonara009/test-98c744a4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use sayonara009/test-98c744a4 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("sayonara009/test-98c744a4", dtype=torch.bfloat16, device_map="cuda") prompt = "lora" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
Diffusion Model - Real Training
Trained using native diffusion training with real dataset.
- Base model: cagliostrolab/animagine-xl-4.0
- Model type: sdxl
- Training steps: 561
- Final loss: 1.9970437288284302
- Training method: Native (not Docker)
- Dataset: Real images from training data
Training Details
- LR Finder: Used offers-compatible LR finding
- LoRA Configuration: Optimized for sdxl
- Quality Score: 0.5025994367046293
Usage
Use with diffusers library or ComfyUI.
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Model tree for sayonara009/test-98c744a4
Base model
stabilityai/stable-diffusion-xl-base-1.0 Finetuned
cagliostrolab/animagine-xl-4.0