Instructions to use quarterturn/moss_danbooru40k_v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use quarterturn/moss_danbooru40k_v1 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("OpenMOSS-Team/MOSS-Image-SFT", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("quarterturn/moss_danbooru40k_v1") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
A moss image sft bf16 rank 64 style LoRA trained on my danbooru 1024 e/q dataset.
- Downloads last month
- 250
Inference Providers NEW
This model isn't deployed by any Inference Provider. ๐ Ask for provider support
Model tree for quarterturn/moss_danbooru40k_v1
Base model
OpenMOSS-Team/MOSS-Image-Base Finetuned
OpenMOSS-Team/MOSS-Image-SFT