Instructions to use Rofla/LDA_Train_Rofla_DataSet_Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Rofla/LDA_Train_Rofla_DataSet_Model with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Rofla/LDA_Train_Rofla_DataSet_Model", torch_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:
- 172cc0cc4fd8f1fdb08796b414fa1bd423f9c2a0bf29ff9229f9016e34b38b58
- Size of remote file:
- 334 MB
- SHA256:
- 60831191b1f1d9ff16efea4b1862c3b752e900ff7f9dae1e02e64495aed8945b
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