Instructions to use Mimi1782/ROSEWOOD with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Mimi1782/ROSEWOOD with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Mimi1782/ROSEWOOD", torch_dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
metadata
license: openrail
datasets:
- opendatalab/ChartVerse-SFT-1.8M
language:
- dv
metrics:
- brier_score
base_model:
- Tongyi-MAI/Z-Image
new_version: Qwen/Qwen3-TTS-12Hz-1.7B-CustomVoice
pipeline_tag: image-segmentation
library_name: diffusers
tags:
- art