Instructions to use SurenaSa/IOAI2024_CV_Problem_baseline with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use SurenaSa/IOAI2024_CV_Problem_baseline with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("SurenaSa/IOAI2024_CV_Problem_baseline", 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
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 0ffd32c2264f21940290473c84b14094e2308f16d5d1bb28ba63bd5dd2812e9e
- Size of remote file:
- 1.72 GB
- SHA256:
- 495fa7b08b8aee3275d91d3e64ebb9b92c6eaf4caba1bc5dc09be12fc087ba6d
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