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
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
AttnAddedKVProcessor
[[autodoc]] models.attention_processor.AttnAddedKVProcessor
AttnAddedKVProcessor2_0
[[autodoc]] models.attention_processor.AttnAddedKVProcessor2_0
CrossFrameAttnProcessor
[[autodoc]] pipelines.text_to_video_synthesis.pipeline_text_to_video_zero.CrossFrameAttnProcessor
CustomDiffusionAttnProcessor
[[autodoc]] models.attention_processor.CustomDiffusionAttnProcessor
CustomDiffusionAttnProcessor2_0
[[autodoc]] models.attention_processor.CustomDiffusionAttnProcessor2_0
CustomDiffusionXFormersAttnProcessor
[[autodoc]] models.attention_processor.CustomDiffusionXFormersAttnProcessor
FusedAttnProcessor2_0
[[autodoc]] models.attention_processor.FusedAttnProcessor2_0
SlicedAttnProcessor
[[autodoc]] models.attention_processor.SlicedAttnProcessor
SlicedAttnAddedKVProcessor
[[autodoc]] models.attention_processor.SlicedAttnAddedKVProcessor
XFormersAttnProcessor
[[autodoc]] models.attention_processor.XFormersAttnProcessor
AttnProcessorNPU
[[autodoc]] models.attention_processor.AttnProcessorNPU