Text-to-Image
Diffusers
TensorBoard
Safetensors
StableDiffusionPipeline
dreambooth
diffusers-training
stable-diffusion
stable-diffusion-diffusers
Instructions to use danielajisafe/model_checkpoints with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use danielajisafe/model_checkpoints with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("danielajisafe/model_checkpoints", 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:
- 0a37ea5fc8c8b9f5135b04797a95720a33cbd3fc8410c84f4b7501aabd8904bd
- Size of remote file:
- 492 MB
- SHA256:
- 0d3d331f7e9e345895180b39ebb509f1340a310150bcd6caf0ce4e3ebfb6eb61
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