Instructions to use swiftydave/db_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use swiftydave/db_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("swiftydave/db_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:
- d0d3b67d5b97bade6db05fcb013a58ccbad02d93c37c45919814d5a375da2e59
- Size of remote file:
- 335 MB
- SHA256:
- 39fb36fb5b8d1bd1292b0c8917fde7204da42d30ca9222dcc7cfb0b062309d91
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