Text-to-Image
Diffusers
Safetensors
StableDiffusionPipeline
dreambooth
diffusers-training
stable-diffusion
stable-diffusion-diffusers
Instructions to use camgitblame/the_shining with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use camgitblame/the_shining with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("camgitblame/the_shining", dtype=torch.bfloat16, device_map="cuda") prompt = "a photo of sks theshining" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 371031dea1eb07cc0f5f3db1f713888f8c1322311b38a4b0c55f4180846dd87e
- Size of remote file:
- 492 MB
- SHA256:
- 8d9d11bc9332a85c56ecdd40be69461b766e5899e1d5385dd6267917a1d37a2c
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