Instructions to use Prajeevan/akshyaid with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Prajeevan/akshyaid with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Prajeevan/akshyaid", dtype=torch.bfloat16, device_map="cuda") prompt = "akshyaiD" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 36b954ec8e09b2b2e34ced79991b46ce5f30bc7138a5c888c6602fd3faede5a8
- Size of remote file:
- 2.13 GB
- SHA256:
- e1a37eca1d501290758a7a54e4dff2d0110aa30898472dab541cb13fd99a971a
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