Instructions to use tm-hf-repo/sdci with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use tm-hf-repo/sdci with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("undefined", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("tm-hf-repo/sdci") prompt = "sdci" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
sdci
Model description
using seedream, "convert this to a children's storybook illustration style"
Trigger words
You should use sdci to trigger the image generation.
Download model
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.
INPUT
Prompt: sdci
Prompt : sdci,maintain the same skintone
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