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
PEFT
Diffusers supports loading adapters such as LoRA with the PEFT library with the [~loaders.peft.PeftAdapterMixin] class. This allows modeling classes in Diffusers like [UNet2DConditionModel], [SD3Transformer2DModel] to operate with an adapter.
Refer to the Inference with PEFT tutorial for an overview of how to use PEFT in Diffusers for inference.
PeftAdapterMixin
[[autodoc]] loaders.peft.PeftAdapterMixin