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
VAE
vae_roundtrip.py Demonstrates the use of a VAE by roundtripping an image through the encoder and decoder. Original and reconstructed images are displayed side by side.
cd examples/research_projects/vae
python vae_roundtrip.py \
--pretrained_model_name_or_path="runwayml/stable-diffusion-v1-5" \
--subfolder="vae" \
--input_image="/path/to/your/input.png"