Text-to-Image
Diffusers
TensorBoard
Safetensors
StableDiffusionPipeline
dreambooth
diffusers-training
stable-diffusion
stable-diffusion-diffusers
Instructions to use NadaGh/working with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use NadaGh/working with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("NadaGh/working", dtype=torch.bfloat16, device_map="cuda") prompt = "tst chair" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
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Download diffusers/docs/source/en/api/utilities.md from NadaGh/working: direct link, hf CLI and curl.
- Browser
- Download file 1.02 kB
-
https://huggingface.co/NadaGh/working/resolve/main/diffusers/docs/source/en/api/utilities.md
- Command line
-
hf download hf://NadaGh/working/diffusers/docs/source/en/api/utilities.md
-
curl -L -o utilities.md https://huggingface.co/NadaGh/working/resolve/main/diffusers/docs/source/en/api/utilities.md
1.02 kB
Utilities
Utility and helper functions for working with 🤗 Diffusers.
numpy_to_pil
[[autodoc]] utils.numpy_to_pil
pt_to_pil
[[autodoc]] utils.pt_to_pil
load_image
[[autodoc]] utils.load_image
export_to_gif
[[autodoc]] utils.export_to_gif
export_to_video
[[autodoc]] utils.export_to_video
make_image_grid
[[autodoc]] utils.make_image_grid
randn_tensor
[[autodoc]] utils.torch_utils.randn_tensor