Instructions to use Aminrabi/diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Aminrabi/diffusers with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Aminrabi/diffusers", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
Attention Processor
An attention processor is a class for applying different types of attention mechanisms.
AttnProcessor
[[autodoc]] models.attention_processor.AttnProcessor
AttnProcessor2_0
[[autodoc]] models.attention_processor.AttnProcessor2_0
LoRAAttnProcessor
[[autodoc]] models.attention_processor.LoRAAttnProcessor
LoRAAttnProcessor2_0
[[autodoc]] models.attention_processor.LoRAAttnProcessor2_0
CustomDiffusionAttnProcessor
[[autodoc]] models.attention_processor.CustomDiffusionAttnProcessor
AttnAddedKVProcessor
[[autodoc]] models.attention_processor.AttnAddedKVProcessor
AttnAddedKVProcessor2_0
[[autodoc]] models.attention_processor.AttnAddedKVProcessor2_0
LoRAAttnAddedKVProcessor
[[autodoc]] models.attention_processor.LoRAAttnAddedKVProcessor
XFormersAttnProcessor
[[autodoc]] models.attention_processor.XFormersAttnProcessor
LoRAXFormersAttnProcessor
[[autodoc]] models.attention_processor.LoRAXFormersAttnProcessor
CustomDiffusionXFormersAttnProcessor
[[autodoc]] models.attention_processor.CustomDiffusionXFormersAttnProcessor
SlicedAttnProcessor
[[autodoc]] models.attention_processor.SlicedAttnProcessor
SlicedAttnAddedKVProcessor
[[autodoc]] models.attention_processor.SlicedAttnAddedKVProcessor