Text-to-Image
Diffusers
TensorBoard
Safetensors
StableDiffusionPipeline
dreambooth
diffusers-training
stable-diffusion
stable-diffusion-diffusers
Instructions to use KCS97/dog2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use KCS97/dog2 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/dog2", dtype=torch.bfloat16, device_map="cuda") prompt = "a photo of sks dog" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 6d67b63c4374d126f135db11f9e534a181c7fd65df6a4bc71181d1ade85165e8
- Size of remote file:
- 6.88 GB
- SHA256:
- 15015e2e63f2ecba5c56f9006a7688bbad00693da216c66294751f9a1b49a957
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