Diffusers
Safetensors
CondDDIMPipeline
downscaling
ERA5 - COSMO-REA6
reanalysis data
wind velocities
diffusion
superresolution
Instructions to use lschmidt/ddim-dsc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use lschmidt/ddim-dsc with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("lschmidt/ddim-dsc", 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
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README.md
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#
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batch_size = 1
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in_channels = 6
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sample_size = 160
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sequence_len = 3
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lres_image = torch.randn((sequence_len, in_channels, sample_size, sample_size)).to(pipe.device)
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pipe(image =inputs)
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#
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batch_size = 1
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in_channels = 6
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sequence_len = 3
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#
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lres_image = torch.randn((sequence_len, in_channels, sample_size, sample_size)).to(pipe.device)
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pipe(image=lres_image)
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