Instructions to use sokobanni/samik-test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use sokobanni/samik-test with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("sokobanni/samik-test", dtype=torch.bfloat16, device_map="cuda") prompt = "samik" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 6bb60c85eb86be8e054e9ab8a9be6b4cee723b5d7bb37e885e0bda33fd72ce7c
- Size of remote file:
- 1.36 GB
- SHA256:
- cc3f823cbc38d720df169faa3e55ddd29dd653bc18ea68d0da970583673fb5e3
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