Instructions to use camenduru/PASD with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use camenduru/PASD with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("camenduru/PASD", 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
thanks to yangxy ❤
Browse files- pasd.zip +3 -0
- pasd_light.zip +3 -0
- pasd_light_rrdb.zip +3 -0
- pasd_rrdb.zip +3 -0
pasd.zip
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version https://git-lfs.github.com/spec/v1
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oid sha256:48eb5f434791f3d0d7c1b36c0aaf1040d935c0a065cae96d7e35336af9df93b7
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size 5453737067
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pasd_light.zip
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version https://git-lfs.github.com/spec/v1
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oid sha256:f85fc8001c82c2555fc50bfe1faa1690c6778bba822bdc6ab0d3a8d53744188a
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size 4641151617
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pasd_light_rrdb.zip
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version https://git-lfs.github.com/spec/v1
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oid sha256:754ccb0a0931bea7a600822850b8c60c6ee0707e1d3fe0a75c49d8c2fd7371ec
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size 4641878893
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pasd_rrdb.zip
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version https://git-lfs.github.com/spec/v1
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oid sha256:4f17f043d869ff425eebf02ffa77b2f720d98dc7337b739ce2849e5e9fd7719b
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size 5454248591
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