Text-to-Image
Diffusers
TensorBoard
Safetensors
StableDiffusionPipeline
dreambooth
diffusers-training
stable-diffusion
stable-diffusion-diffusers
Instructions to use KCS97/candle with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use KCS97/candle with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("KCS97/candle", dtype=torch.bfloat16, device_map="cuda") prompt = "a photo of sks candle" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 92889cdf2df9d7e0356254454b86d4b6e49731b3c631b99146d898cc51f88a90
- Size of remote file:
- 6.88 GB
- SHA256:
- 425b1ab8b1174abfa32dcb77b3c3085c88c6f05a8d653ce713e3801eeeb9f129
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