Instructions to use KORMo-VL/KORMo-VL-Diffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use KORMo-VL/KORMo-VL-Diffusion with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("KORMo-VL/KORMo-VL-Diffusion", 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
- Xet hash:
- e95faaa4c746b3691529e00e687f67da3c4b1e9011d3c825ceeb0f3e941a9eb8
- Size of remote file:
- 508 MB
- SHA256:
- ab1b61103959913d6c7e628cf793dbb2ca4726a40a3b3ae206c52b8e75bf6f08
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