Instructions to use Omerdor/dry_samples_train with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Omerdor/dry_samples_train with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Omerdor/dry_samples_train", 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
Epoch 39
Browse files- .gitattributes +3 -0
- logs/train_example/events.out.tfevents.1668092652.research-vm-1.7962.0 +2 -2
- samples/0031.png +3 -0
- samples/0035.png +3 -0
- samples/0039.png +3 -0
- unet/diffusion_pytorch_model.bin +1 -1
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