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:
- 96803f4bdc71a06f3b159dcb53ce8a69fedc8e476d55aee6030a65d2da225d66
- Size of remote file:
- 2 GB
- SHA256:
- e4923299e6a363b349ec61ff064915fe55b9460b0c5817ec56d1367dbfa72e9c
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